WorldWideScience

Sample records for penalized multivariate regression

  1. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  2. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.

    2010-08-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  3. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.; Carroll, R.J.; Wand, M.P.

    2010-01-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  4. Regularized multivariate regression models with skew-t error distributions

    KAUST Repository

    Chen, Lianfu; Pourahmadi, Mohsen; Maadooliat, Mehdi

    2014-01-01

    We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both

  5. Penalized variable selection in competing risks regression.

    Science.gov (United States)

    Fu, Zhixuan; Parikh, Chirag R; Zhou, Bingqing

    2017-07-01

    Penalized variable selection methods have been extensively studied for standard time-to-event data. Such methods cannot be directly applied when subjects are at risk of multiple mutually exclusive events, known as competing risks. The proportional subdistribution hazard (PSH) model proposed by Fine and Gray (J Am Stat Assoc 94:496-509, 1999) has become a popular semi-parametric model for time-to-event data with competing risks. It allows for direct assessment of covariate effects on the cumulative incidence function. In this paper, we propose a general penalized variable selection strategy that simultaneously handles variable selection and parameter estimation in the PSH model. We rigorously establish the asymptotic properties of the proposed penalized estimators and modify the coordinate descent algorithm for implementation. Simulation studies are conducted to demonstrate the good performance of the proposed method. Data from deceased donor kidney transplants from the United Network of Organ Sharing illustrate the utility of the proposed method.

  6. Regularized multivariate regression models with skew-t error distributions

    KAUST Repository

    Chen, Lianfu

    2014-06-01

    We consider regularization of the parameters in multivariate linear regression models with the errors having a multivariate skew-t distribution. An iterative penalized likelihood procedure is proposed for constructing sparse estimators of both the regression coefficient and inverse scale matrices simultaneously. The sparsity is introduced through penalizing the negative log-likelihood by adding L1-penalties on the entries of the two matrices. Taking advantage of the hierarchical representation of skew-t distributions, and using the expectation conditional maximization (ECM) algorithm, we reduce the problem to penalized normal likelihood and develop a procedure to minimize the ensuing objective function. Using a simulation study the performance of the method is assessed, and the methodology is illustrated using a real data set with a 24-dimensional response vector. © 2014 Elsevier B.V.

  7. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  8. Advanced colorectal neoplasia risk stratification by penalized logistic regression.

    Science.gov (United States)

    Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

    2016-08-01

    Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

  9. Bayesian Analysis for Penalized Spline Regression Using WinBUGS

    Directory of Open Access Journals (Sweden)

    Ciprian M. Crainiceanu

    2005-09-01

    Full Text Available Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.

  10. Penalized regression procedures for variable selection in the potential outcomes framework.

    Science.gov (United States)

    Ghosh, Debashis; Zhu, Yeying; Coffman, Donna L

    2015-05-10

    A recent topic of much interest in causal inference is model selection. In this article, we describe a framework in which to consider penalized regression approaches to variable selection for causal effects. The framework leads to a simple 'impute, then select' class of procedures that is agnostic to the type of imputation algorithm as well as penalized regression used. It also clarifies how model selection involves a multivariate regression model for causal inference problems and that these methods can be applied for identifying subgroups in which treatment effects are homogeneous. Analogies and links with the literature on machine learning methods, missing data, and imputation are drawn. A difference least absolute shrinkage and selection operator algorithm is defined, along with its multiple imputation analogs. The procedures are illustrated using a well-known right-heart catheterization dataset. Copyright © 2015 John Wiley & Sons, Ltd.

  11. Examination of influential observations in penalized spline regression

    Science.gov (United States)

    Türkan, Semra

    2013-10-01

    In parametric or nonparametric regression models, the results of regression analysis are affected by some anomalous observations in the data set. Thus, detection of these observations is one of the major steps in regression analysis. These observations are precisely detected by well-known influence measures. Pena's statistic is one of them. In this study, Pena's approach is formulated for penalized spline regression in terms of ordinary residuals and leverages. The real data and artificial data are used to see illustrate the effectiveness of Pena's statistic as to Cook's distance on detecting influential observations. The results of the study clearly reveal that the proposed measure is superior to Cook's Distance to detect these observations in large data set.

  12. Multivariate Regression Analysis and Slaughter Livestock,

    Science.gov (United States)

    AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

  13. Polygenic scores via penalized regression on summary statistics.

    Science.gov (United States)

    Mak, Timothy Shin Heng; Porsch, Robert Milan; Choi, Shing Wan; Zhou, Xueya; Sham, Pak Chung

    2017-09-01

    Polygenic scores (PGS) summarize the genetic contribution of a person's genotype to a disease or phenotype. They can be used to group participants into different risk categories for diseases, and are also used as covariates in epidemiological analyses. A number of possible ways of calculating PGS have been proposed, and recently there is much interest in methods that incorporate information available in published summary statistics. As there is no inherent information on linkage disequilibrium (LD) in summary statistics, a pertinent question is how we can use LD information available elsewhere to supplement such analyses. To answer this question, we propose a method for constructing PGS using summary statistics and a reference panel in a penalized regression framework, which we call lassosum. We also propose a general method for choosing the value of the tuning parameter in the absence of validation data. In our simulations, we showed that pseudovalidation often resulted in prediction accuracy that is comparable to using a dataset with validation phenotype and was clearly superior to the conservative option of setting the tuning parameter of lassosum to its lowest value. We also showed that lassosum achieved better prediction accuracy than simple clumping and P-value thresholding in almost all scenarios. It was also substantially faster and more accurate than the recently proposed LDpred. © 2017 WILEY PERIODICALS, INC.

  14. Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

    Science.gov (United States)

    Li, Yanming; Nan, Bin; Zhu, Ji

    2015-06-01

    We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.

  15. Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

    Science.gov (United States)

    Islamiyati, A.; Fatmawati; Chamidah, N.

    2018-03-01

    The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

  16. Penalized estimation for competing risks regression with applications to high-dimensional covariates

    DEFF Research Database (Denmark)

    Ambrogi, Federico; Scheike, Thomas H.

    2016-01-01

    of competing events. The direct binomial regression model of Scheike and others (2008. Predicting cumulative incidence probability by direct binomial regression. Biometrika 95: (1), 205-220) is reformulated in a penalized framework to possibly fit a sparse regression model. The developed approach is easily...... Research 19: (1), 29-51), the research regarding competing risks is less developed (Binder and others, 2009. Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics 25: (7), 890-896). The aim of this work is to consider how to do penalized regression in the presence...... implementable using existing high-performance software to do penalized regression. Results from simulation studies are presented together with an application to genomic data when the endpoint is progression-free survival. An R function is provided to perform regularized competing risks regression according...

  17. Regression Models For Multivariate Count Data.

    Science.gov (United States)

    Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

    2017-01-01

    Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

  18. Bayesian Inference of a Multivariate Regression Model

    Directory of Open Access Journals (Sweden)

    Marick S. Sinay

    2014-01-01

    Full Text Available We explore Bayesian inference of a multivariate linear regression model with use of a flexible prior for the covariance structure. The commonly adopted Bayesian setup involves the conjugate prior, multivariate normal distribution for the regression coefficients and inverse Wishart specification for the covariance matrix. Here we depart from this approach and propose a novel Bayesian estimator for the covariance. A multivariate normal prior for the unique elements of the matrix logarithm of the covariance matrix is considered. Such structure allows for a richer class of prior distributions for the covariance, with respect to strength of beliefs in prior location hyperparameters, as well as the added ability, to model potential correlation amongst the covariance structure. The posterior moments of all relevant parameters of interest are calculated based upon numerical results via a Markov chain Monte Carlo procedure. The Metropolis-Hastings-within-Gibbs algorithm is invoked to account for the construction of a proposal density that closely matches the shape of the target posterior distribution. As an application of the proposed technique, we investigate a multiple regression based upon the 1980 High School and Beyond Survey.

  19. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  20. AN APPLICATION OF FUNCTIONAL MULTIVARIATE REGRESSION MODEL TO MULTICLASS CLASSIFICATION

    OpenAIRE

    Krzyśko, Mirosław; Smaga, Łukasz

    2017-01-01

    In this paper, the scale response functional multivariate regression model is considered. By using the basis functions representation of functional predictors and regression coefficients, this model is rewritten as a multivariate regression model. This representation of the functional multivariate regression model is used for multiclass classification for multivariate functional data. Computational experiments performed on real labelled data sets demonstrate the effectiveness of the proposed ...

  1. Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

    Energy Technology Data Exchange (ETDEWEB)

    Bramer, L. M.; Rounds, J.; Burleyson, C. D.; Fortin, D.; Hathaway, J.; Rice, J.; Kraucunas, I.

    2017-11-01

    Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.

  2. Sunspot Cycle Prediction Using Multivariate Regression and Binary ...

    Indian Academy of Sciences (India)

    49

    Multivariate regression model has been derived based on the available cycles 1 .... The flare index correlates well with various parameters of the solar activity. ...... 32) Sabarinath A and Anilkumar A K 2011 A stochastic prediction model for the.

  3. A Scalable Local Algorithm for Distributed Multivariate Regression

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm can be used for distributed...

  4. Multivariate Regression of Liver on Intestine of Mice: A ...

    African Journals Online (AJOL)

    Multivariate Regression of Liver on Intestine of Mice: A Chemotherapeutic Evaluation of Plant ... Using an analysis of covariance model, the effects ... The findings revealed, with the aid of likelihood-ratio statistic, a marked improvement in

  5. An Efficient Local Algorithm for Distributed Multivariate Regression

    Data.gov (United States)

    National Aeronautics and Space Administration — This paper offers a local distributed algorithm for multivariate regression in large peer-to-peer environments. The algorithm is designed for distributed...

  6. A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data

    KAUST Repository

    Gazioglu, Suzan; Wei, Jiawei; Jennings, Elizabeth M.; Carroll, Raymond J.

    2013-01-01

    Primary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.

  7. A Note on Penalized Regression Spline Estimation in the Secondary Analysis of Case-Control Data

    KAUST Repository

    Gazioglu, Suzan

    2013-05-25

    Primary analysis of case-control studies focuses on the relationship between disease (D) and a set of covariates of interest (Y, X). A secondary application of the case-control study, often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated due to the case-control sampling, and to avoid the biased sampling that arises from the design, it is typical to use the control data only. In this paper, we develop penalized regression spline methodology that uses all the data, and improves precision of estimation compared to using only the controls. A simulation study and an empirical example are used to illustrate the methodology.

  8. A robust regression based on weighted LSSVM and penalized trimmed squares

    International Nuclear Information System (INIS)

    Liu, Jianyong; Wang, Yong; Fu, Chengqun; Guo, Jie; Yu, Qin

    2016-01-01

    Least squares support vector machine (LS-SVM) for nonlinear regression is sensitive to outliers in the field of machine learning. Weighted LS-SVM (WLS-SVM) overcomes this drawback by adding weight to each training sample. However, as the number of outliers increases, the accuracy of WLS-SVM may decrease. In order to improve the robustness of WLS-SVM, a new robust regression method based on WLS-SVM and penalized trimmed squares (WLSSVM–PTS) has been proposed. The algorithm comprises three main stages. The initial parameters are obtained by least trimmed squares at first. Then, the significant outliers are identified and eliminated by the Fast-PTS algorithm. The remaining samples with little outliers are estimated by WLS-SVM at last. The statistical tests of experimental results carried out on numerical datasets and real-world datasets show that the proposed WLSSVM–PTS is significantly robust than LS-SVM, WLS-SVM and LSSVM–LTS.

  9. Asymptotics of Multivariate Regression with Consecutively Added Dependent Varibles

    NARCIS (Netherlands)

    Raats, V.M.; van der Genugten, B.B.; Moors, J.J.A.

    2004-01-01

    We consider multivariate regression where new dependent variables are consecutively added during the experiment (or in time).So, viewed at the end of the experiment, the number of observations decreases with each added variable. The explanatory variables are observed throughout.In a previous paper

  10. Multivariate Local Polynomial Regression with Application to Shenzhen Component Index

    Directory of Open Access Journals (Sweden)

    Liyun Su

    2011-01-01

    Full Text Available This study attempts to characterize and predict stock index series in Shenzhen stock market using the concepts of multivariate local polynomial regression. Based on nonlinearity and chaos of the stock index time series, multivariate local polynomial prediction methods and univariate local polynomial prediction method, all of which use the concept of phase space reconstruction according to Takens' Theorem, are considered. To fit the stock index series, the single series changes into bivariate series. To evaluate the results, the multivariate predictor for bivariate time series based on multivariate local polynomial model is compared with univariate predictor with the same Shenzhen stock index data. The numerical results obtained by Shenzhen component index show that the prediction mean squared error of the multivariate predictor is much smaller than the univariate one and is much better than the existed three methods. Even if the last half of the training data are used in the multivariate predictor, the prediction mean squared error is smaller than the univariate predictor. Multivariate local polynomial prediction model for nonsingle time series is a useful tool for stock market price prediction.

  11. AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

    Science.gov (United States)

    Yu, Wenbao; Park, Taesung

    2014-01-01

    It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

  12. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

  13. REGSTEP - stepwise multivariate polynomial regression with singular extensions

    International Nuclear Information System (INIS)

    Davierwalla, D.M.

    1977-09-01

    The program REGSTEP determines a polynomial approximation, in the least squares sense, to tabulated data. The polynomial may be univariate or multivariate. The computational method is that of stepwise regression. A variable is inserted into the regression basis if it is significant with respect to an appropriate F-test at a preselected risk level. In addition, should a variable already in the basis, become nonsignificant (again with respect to an appropriate F-test) after the entry of a new variable, it is expelled from the model. Thus only significant variables are retained in the model. Although written expressly to be incorporated into CORCOD, a code for predicting nuclear cross sections for given values of power, temperature, void fractions, Boron content etc. there is nothing to limit the use of REGSTEP to nuclear applications, as the examples demonstrate. A separate version has been incorporated into RSYST for the general user. (Auth.)

  14. Collision prediction models using multivariate Poisson-lognormal regression.

    Science.gov (United States)

    El-Basyouny, Karim; Sayed, Tarek

    2009-07-01

    This paper advocates the use of multivariate Poisson-lognormal (MVPLN) regression to develop models for collision count data. The MVPLN approach presents an opportunity to incorporate the correlations across collision severity levels and their influence on safety analyses. The paper introduces a new multivariate hazardous location identification technique, which generalizes the univariate posterior probability of excess that has been commonly proposed and applied in the literature. In addition, the paper presents an alternative approach for quantifying the effect of the multivariate structure on the precision of expected collision frequency. The MVPLN approach is compared with the independent (separate) univariate Poisson-lognormal (PLN) models with respect to model inference, goodness-of-fit, identification of hot spots and precision of expected collision frequency. The MVPLN is modeled using the WinBUGS platform which facilitates computation of posterior distributions as well as providing a goodness-of-fit measure for model comparisons. The results indicate that the estimates of the extra Poisson variation parameters were considerably smaller under MVPLN leading to higher precision. The improvement in precision is due mainly to the fact that MVPLN accounts for the correlation between the latent variables representing property damage only (PDO) and injuries plus fatalities (I+F). This correlation was estimated at 0.758, which is highly significant, suggesting that higher PDO rates are associated with higher I+F rates, as the collision likelihood for both types is likely to rise due to similar deficiencies in roadway design and/or other unobserved factors. In terms of goodness-of-fit, the MVPLN model provided a superior fit than the independent univariate models. The multivariate hazardous location identification results demonstrated that some hazardous locations could be overlooked if the analysis was restricted to the univariate models.

  15. Multivariate Frequency-Severity Regression Models in Insurance

    Directory of Open Access Journals (Sweden)

    Edward W. Frees

    2016-02-01

    Full Text Available In insurance and related industries including healthcare, it is common to have several outcome measures that the analyst wishes to understand using explanatory variables. For example, in automobile insurance, an accident may result in payments for damage to one’s own vehicle, damage to another party’s vehicle, or personal injury. It is also common to be interested in the frequency of accidents in addition to the severity of the claim amounts. This paper synthesizes and extends the literature on multivariate frequency-severity regression modeling with a focus on insurance industry applications. Regression models for understanding the distribution of each outcome continue to be developed yet there now exists a solid body of literature for the marginal outcomes. This paper contributes to this body of literature by focusing on the use of a copula for modeling the dependence among these outcomes; a major advantage of this tool is that it preserves the body of work established for marginal models. We illustrate this approach using data from the Wisconsin Local Government Property Insurance Fund. This fund offers insurance protection for (i property; (ii motor vehicle; and (iii contractors’ equipment claims. In addition to several claim types and frequency-severity components, outcomes can be further categorized by time and space, requiring complex dependency modeling. We find significant dependencies for these data; specifically, we find that dependencies among lines are stronger than the dependencies between the frequency and average severity within each line.

  16. A generalized multivariate regression model for modelling ocean wave heights

    Science.gov (United States)

    Wang, X. L.; Feng, Y.; Swail, V. R.

    2012-04-01

    In this study, a generalized multivariate linear regression model is developed to represent the relationship between 6-hourly ocean significant wave heights (Hs) and the corresponding 6-hourly mean sea level pressure (MSLP) fields. The model is calibrated using the ERA-Interim reanalysis of Hs and MSLP fields for 1981-2000, and is validated using the ERA-Interim reanalysis for 2001-2010 and ERA40 reanalysis of Hs and MSLP for 1958-2001. The performance of the fitted model is evaluated in terms of Pierce skill score, frequency bias index, and correlation skill score. Being not normally distributed, wave heights are subjected to a data adaptive Box-Cox transformation before being used in the model fitting. Also, since 6-hourly data are being modelled, lag-1 autocorrelation must be and is accounted for. The models with and without Box-Cox transformation, and with and without accounting for autocorrelation, are inter-compared in terms of their prediction skills. The fitted MSLP-Hs relationship is then used to reconstruct historical wave height climate from the 6-hourly MSLP fields taken from the Twentieth Century Reanalysis (20CR, Compo et al. 2011), and to project possible future wave height climates using CMIP5 model simulations of MSLP fields. The reconstructed and projected wave heights, both seasonal means and maxima, are subject to a trend analysis that allows for non-linear (polynomial) trends.

  17. A Two-Stage Penalized Logistic Regression Approach to Case-Control Genome-Wide Association Studies

    Directory of Open Access Journals (Sweden)

    Jingyuan Zhao

    2012-01-01

    Full Text Available We propose a two-stage penalized logistic regression approach to case-control genome-wide association studies. This approach consists of a screening stage and a selection stage. In the screening stage, main-effect and interaction-effect features are screened by using L1-penalized logistic like-lihoods. In the selection stage, the retained features are ranked by the logistic likelihood with the smoothly clipped absolute deviation (SCAD penalty (Fan and Li, 2001 and Jeffrey’s Prior penalty (Firth, 1993, a sequence of nested candidate models are formed, and the models are assessed by a family of extended Bayesian information criteria (J. Chen and Z. Chen, 2008. The proposed approach is applied to the analysis of the prostate cancer data of the Cancer Genetic Markers of Susceptibility (CGEMS project in the National Cancer Institute, USA. Simulation studies are carried out to compare the approach with the pair-wise multiple testing approach (Marchini et al. 2005 and the LASSO-patternsearch algorithm (Shi et al. 2007.

  18. Multivariate Regression of Liver on Intestine of Mice: A ...

    African Journals Online (AJOL)

    FIRST LADY

    pairs recovered. Linear, semi-logarithmic and logarithmic-logarithmic (log- log) regressions were performed. He chose the log-log curves because its variance was more uniform. The statistical comparison of .... E(U1| U2 = u2) is the regression function of U1 on U2, and Var (U1|U2 = u2) is the conditional covariance matrix.

  19. Real estate value prediction using multivariate regression models

    Science.gov (United States)

    Manjula, R.; Jain, Shubham; Srivastava, Sharad; Rajiv Kher, Pranav

    2017-11-01

    The real estate market is one of the most competitive in terms of pricing and the same tends to vary significantly based on a lot of factors, hence it becomes one of the prime fields to apply the concepts of machine learning to optimize and predict the prices with high accuracy. Therefore in this paper, we present various important features to use while predicting housing prices with good accuracy. We have described regression models, using various features to have lower Residual Sum of Squares error. While using features in a regression model some feature engineering is required for better prediction. Often a set of features (multiple regressions) or polynomial regression (applying a various set of powers in the features) is used for making better model fit. For these models are expected to be susceptible towards over fitting ridge regression is used to reduce it. This paper thus directs to the best application of regression models in addition to other techniques to optimize the result.

  20. IPF-LASSO: Integrative L1-Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

    Directory of Open Access Journals (Sweden)

    Anne-Laure Boulesteix

    2017-01-01

    Full Text Available As modern biotechnologies advance, it has become increasingly frequent that different modalities of high-dimensional molecular data (termed “omics” data in this paper, such as gene expression, methylation, and copy number, are collected from the same patient cohort to predict the clinical outcome. While prediction based on omics data has been widely studied in the last fifteen years, little has been done in the statistical literature on the integration of multiple omics modalities to select a subset of variables for prediction, which is a critical task in personalized medicine. In this paper, we propose a simple penalized regression method to address this problem by assigning different penalty factors to different data modalities for feature selection and prediction. The penalty factors can be chosen in a fully data-driven fashion by cross-validation or by taking practical considerations into account. In simulation studies, we compare the prediction performance of our approach, called IPF-LASSO (Integrative LASSO with Penalty Factors and implemented in the R package ipflasso, with the standard LASSO and sparse group LASSO. The use of IPF-LASSO is also illustrated through applications to two real-life cancer datasets. All data and codes are available on the companion website to ensure reproducibility.

  1. Nonparametric Regression Estimation for Multivariate Null Recurrent Processes

    Directory of Open Access Journals (Sweden)

    Biqing Cai

    2015-04-01

    Full Text Available This paper discusses nonparametric kernel regression with the regressor being a \\(d\\-dimensional \\(\\beta\\-null recurrent process in presence of conditional heteroscedasticity. We show that the mean function estimator is consistent with convergence rate \\(\\sqrt{n(Th^{d}}\\, where \\(n(T\\ is the number of regenerations for a \\(\\beta\\-null recurrent process and the limiting distribution (with proper normalization is normal. Furthermore, we show that the two-step estimator for the volatility function is consistent. The finite sample performance of the estimate is quite reasonable when the leave-one-out cross validation method is used for bandwidth selection. We apply the proposed method to study the relationship of Federal funds rate with 3-month and 5-year T-bill rates and discover the existence of nonlinearity of the relationship. Furthermore, the in-sample and out-of-sample performance of the nonparametric model is far better than the linear model.

  2. Ultracentrifuge separative power modeling with multivariate regression using covariance matrix

    International Nuclear Information System (INIS)

    Migliavacca, Elder

    2004-01-01

    In this work, the least-squares methodology with covariance matrix is applied to determine a data curve fitting to obtain a performance function for the separative power δU of a ultracentrifuge as a function of variables that are experimentally controlled. The experimental data refer to 460 experiments on the ultracentrifugation process for uranium isotope separation. The experimental uncertainties related with these independent variables are considered in the calculation of the experimental separative power values, determining an experimental data input covariance matrix. The process variables, which significantly influence the δU values are chosen in order to give information on the ultracentrifuge behaviour when submitted to several levels of feed flow rate F, cut θ and product line pressure P p . After the model goodness-of-fit validation, a residual analysis is carried out to verify the assumed basis concerning its randomness and independence and mainly the existence of residual heteroscedasticity with any explained regression model variable. The surface curves are made relating the separative power with the control variables F, θ and P p to compare the fitted model with the experimental data and finally to calculate their optimized values. (author)

  3. Supremum Norm Posterior Contraction and Credible Sets for Nonparametric Multivariate Regression

    NARCIS (Netherlands)

    Yoo, W.W.; Ghosal, S

    2016-01-01

    In the setting of nonparametric multivariate regression with unknown error variance, we study asymptotic properties of a Bayesian method for estimating a regression function f and its mixed partial derivatives. We use a random series of tensor product of B-splines with normal basis coefficients as a

  4. Fourier transform infrared spectroscopic imaging and multivariate regression for prediction of proteoglycan content of articular cartilage.

    Directory of Open Access Journals (Sweden)

    Lassi Rieppo

    Full Text Available Fourier Transform Infrared (FT-IR spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG contents of articular cartilage (AC. However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR and principal component regression (PCR methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O-stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used.

  5. mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

    Science.gov (United States)

    Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

    2015-03-15

    Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Prognostic factorsin inoperable adenocarcinoma of the lung: A multivariate regression analysis of 259 patiens

    DEFF Research Database (Denmark)

    Sørensen, Jens Benn; Badsberg, Jens Henrik; Olsen, Jens

    1989-01-01

    The prognostic factors for survival in advanced adenocarcinoma of the lung were investigated in a consecutive series of 259 patients treated with chemotherapy. Twenty-eight pretreatment variables were investigated by use of Cox's multivariate regression model, including histological subtypes and ...

  7. Depth-weighted robust multivariate regression with application to sparse data

    KAUST Repository

    Dutta, Subhajit; Genton, Marc G.

    2017-01-01

    A robust method for multivariate regression is developed based on robust estimators of the joint location and scatter matrix of the explanatory and response variables using the notion of data depth. The multivariate regression estimator possesses desirable affine equivariance properties, achieves the best breakdown point of any affine equivariant estimator, and has an influence function which is bounded in both the response as well as the predictor variable. To increase the efficiency of this estimator, a re-weighted estimator based on robust Mahalanobis distances of the residual vectors is proposed. In practice, the method is more stable than existing methods that are constructed using subsamples of the data. The resulting multivariate regression technique is computationally feasible, and turns out to perform better than several popular robust multivariate regression methods when applied to various simulated data as well as a real benchmark data set. When the data dimension is quite high compared to the sample size it is still possible to use meaningful notions of data depth along with the corresponding depth values to construct a robust estimator in a sparse setting.

  8. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

    NARCIS (Netherlands)

    Kromhout, D.

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the

  9. Comparing treatment effects after adjustment with multivariable Cox proportional hazards regression and propensity score methods

    NARCIS (Netherlands)

    Martens, Edwin P; de Boer, Anthonius; Pestman, Wiebe R; Belitser, Svetlana V; Stricker, Bruno H Ch; Klungel, Olaf H

    PURPOSE: To compare adjusted effects of drug treatment for hypertension on the risk of stroke from propensity score (PS) methods with a multivariable Cox proportional hazards (Cox PH) regression in an observational study with censored data. METHODS: From two prospective population-based cohort

  10. Depth-weighted robust multivariate regression with application to sparse data

    KAUST Repository

    Dutta, Subhajit

    2017-04-05

    A robust method for multivariate regression is developed based on robust estimators of the joint location and scatter matrix of the explanatory and response variables using the notion of data depth. The multivariate regression estimator possesses desirable affine equivariance properties, achieves the best breakdown point of any affine equivariant estimator, and has an influence function which is bounded in both the response as well as the predictor variable. To increase the efficiency of this estimator, a re-weighted estimator based on robust Mahalanobis distances of the residual vectors is proposed. In practice, the method is more stable than existing methods that are constructed using subsamples of the data. The resulting multivariate regression technique is computationally feasible, and turns out to perform better than several popular robust multivariate regression methods when applied to various simulated data as well as a real benchmark data set. When the data dimension is quite high compared to the sample size it is still possible to use meaningful notions of data depth along with the corresponding depth values to construct a robust estimator in a sparse setting.

  11. Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

    Science.gov (United States)

    Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

    2017-12-01

    The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

  12. High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

    Science.gov (United States)

    Laurens, L M L; Wolfrum, E J

    2013-12-18

    One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

  13. Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

    Science.gov (United States)

    MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

    2005-01-01

    Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

  14. Multivariate nonparametric regression and visualization with R and applications to finance

    CERN Document Server

    Klemelä, Jussi

    2014-01-01

    A modern approach to statistical learning and its applications through visualization methods With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification and regression. The book then introduces and examines various tested and proven visualization techniques for learning samples and functio

  15. Regression Analysis for Multivariate Dependent Count Data Using Convolved Gaussian Processes

    OpenAIRE

    Sofro, A'yunin; Shi, Jian Qing; Cao, Chunzheng

    2017-01-01

    Research on Poisson regression analysis for dependent data has been developed rapidly in the last decade. One of difficult problems in a multivariate case is how to construct a cross-correlation structure and at the meantime make sure that the covariance matrix is positive definite. To address the issue, we propose to use convolved Gaussian process (CGP) in this paper. The approach provides a semi-parametric model and offers a natural framework for modeling common mean structure and covarianc...

  16. Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

    Science.gov (United States)

    Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

    2016-03-01

    From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

  17. Evaluation of Logistic Regression and Multivariate Adaptive Regression Spline Models for Groundwater Potential Mapping Using R and GIS

    Directory of Open Access Journals (Sweden)

    Soyoung Park

    2017-07-01

    Full Text Available This study mapped and analyzed groundwater potential using two different models, logistic regression (LR and multivariate adaptive regression splines (MARS, and compared the results. A spatial database was constructed for groundwater well data and groundwater influence factors. Groundwater well data with a high potential yield of ≥70 m3/d were extracted, and 859 locations (70% were used for model training, whereas the other 365 locations (30% were used for model validation. We analyzed 16 groundwater influence factors including altitude, slope degree, slope aspect, plan curvature, profile curvature, topographic wetness index, stream power index, sediment transport index, distance from drainage, drainage density, lithology, distance from fault, fault density, distance from lineament, lineament density, and land cover. Groundwater potential maps (GPMs were constructed using LR and MARS models and tested using a receiver operating characteristics curve. Based on this analysis, the area under the curve (AUC for the success rate curve of GPMs created using the MARS and LR models was 0.867 and 0.838, and the AUC for the prediction rate curve was 0.836 and 0.801, respectively. This implies that the MARS model is useful and effective for groundwater potential analysis in the study area.

  18. Parameter estimation of multivariate multiple regression model using bayesian with non-informative Jeffreys’ prior distribution

    Science.gov (United States)

    Saputro, D. R. S.; Amalia, F.; Widyaningsih, P.; Affan, R. C.

    2018-05-01

    Bayesian method is a method that can be used to estimate the parameters of multivariate multiple regression model. Bayesian method has two distributions, there are prior and posterior distributions. Posterior distribution is influenced by the selection of prior distribution. Jeffreys’ prior distribution is a kind of Non-informative prior distribution. This prior is used when the information about parameter not available. Non-informative Jeffreys’ prior distribution is combined with the sample information resulting the posterior distribution. Posterior distribution is used to estimate the parameter. The purposes of this research is to estimate the parameters of multivariate regression model using Bayesian method with Non-informative Jeffreys’ prior distribution. Based on the results and discussion, parameter estimation of β and Σ which were obtained from expected value of random variable of marginal posterior distribution function. The marginal posterior distributions for β and Σ are multivariate normal and inverse Wishart. However, in calculation of the expected value involving integral of a function which difficult to determine the value. Therefore, approach is needed by generating of random samples according to the posterior distribution characteristics of each parameter using Markov chain Monte Carlo (MCMC) Gibbs sampling algorithm.

  19. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

    DEFF Research Database (Denmark)

    Tybjærg-Hansen, Anne

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...

  20. PM10 modeling in the Oviedo urban area (Northern Spain) by using multivariate adaptive regression splines

    Science.gov (United States)

    Nieto, Paulino José García; Antón, Juan Carlos Álvarez; Vilán, José Antonio Vilán; García-Gonzalo, Esperanza

    2014-10-01

    The aim of this research work is to build a regression model of the particulate matter up to 10 micrometers in size (PM10) by using the multivariate adaptive regression splines (MARS) technique in the Oviedo urban area (Northern Spain) at local scale. This research work explores the use of a nonparametric regression algorithm known as multivariate adaptive regression splines (MARS) which has the ability to approximate the relationship between the inputs and outputs, and express the relationship mathematically. In this sense, hazardous air pollutants or toxic air contaminants refer to any substance that may cause or contribute to an increase in mortality or serious illness, or that may pose a present or potential hazard to human health. To accomplish the objective of this study, the experimental dataset of nitrogen oxides (NOx), carbon monoxide (CO), sulfur dioxide (SO2), ozone (O3) and dust (PM10) were collected over 3 years (2006-2008) and they are used to create a highly nonlinear model of the PM10 in the Oviedo urban nucleus (Northern Spain) based on the MARS technique. One main objective of this model is to obtain a preliminary estimate of the dependence between PM10 pollutant in the Oviedo urban area at local scale. A second aim is to determine the factors with the greatest bearing on air quality with a view to proposing health and lifestyle improvements. The United States National Ambient Air Quality Standards (NAAQS) establishes the limit values of the main pollutants in the atmosphere in order to ensure the health of healthy people. Firstly, this MARS regression model captures the main perception of statistical learning theory in order to obtain a good prediction of the dependence among the main pollutants in the Oviedo urban area. Secondly, the main advantages of MARS are its capacity to produce simple, easy-to-interpret models, its ability to estimate the contributions of the input variables, and its computational efficiency. Finally, on the basis of

  1. Inference for multivariate regression model based on multiply imputed synthetic data generated via posterior predictive sampling

    Science.gov (United States)

    Moura, Ricardo; Sinha, Bimal; Coelho, Carlos A.

    2017-06-01

    The recent popularity of the use of synthetic data as a Statistical Disclosure Control technique has enabled the development of several methods of generating and analyzing such data, but almost always relying in asymptotic distributions and in consequence being not adequate for small sample datasets. Thus, a likelihood-based exact inference procedure is derived for the matrix of regression coefficients of the multivariate regression model, for multiply imputed synthetic data generated via Posterior Predictive Sampling. Since it is based in exact distributions this procedure may even be used in small sample datasets. Simulation studies compare the results obtained from the proposed exact inferential procedure with the results obtained from an adaptation of Reiters combination rule to multiply imputed synthetic datasets and an application to the 2000 Current Population Survey is discussed.

  2. Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

    Science.gov (United States)

    Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

    2017-02-01

    Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  3. Analysis of Multivariate Experimental Data Using A Simplified Regression Model Search Algorithm

    Science.gov (United States)

    Ulbrich, Norbert Manfred

    2013-01-01

    A new regression model search algorithm was developed in 2011 that may be used to analyze both general multivariate experimental data sets and wind tunnel strain-gage balance calibration data. The new algorithm is a simplified version of a more complex search algorithm that was originally developed at the NASA Ames Balance Calibration Laboratory. The new algorithm has the advantage that it needs only about one tenth of the original algorithm's CPU time for the completion of a search. In addition, extensive testing showed that the prediction accuracy of math models obtained from the simplified algorithm is similar to the prediction accuracy of math models obtained from the original algorithm. The simplified algorithm, however, cannot guarantee that search constraints related to a set of statistical quality requirements are always satisfied in the optimized regression models. Therefore, the simplified search algorithm is not intended to replace the original search algorithm. Instead, it may be used to generate an alternate optimized regression model of experimental data whenever the application of the original search algorithm either fails or requires too much CPU time. Data from a machine calibration of NASA's MK40 force balance is used to illustrate the application of the new regression model search algorithm.

  4. Multivariate linear regression of high-dimensional fMRI data with multiple target variables.

    Science.gov (United States)

    Valente, Giancarlo; Castellanos, Agustin Lage; Vanacore, Gianluca; Formisano, Elia

    2014-05-01

    Multivariate regression is increasingly used to study the relation between fMRI spatial activation patterns and experimental stimuli or behavioral ratings. With linear models, informative brain locations are identified by mapping the model coefficients. This is a central aspect in neuroimaging, as it provides the sought-after link between the activity of neuronal populations and subject's perception, cognition or behavior. Here, we show that mapping of informative brain locations using multivariate linear regression (MLR) may lead to incorrect conclusions and interpretations. MLR algorithms for high dimensional data are designed to deal with targets (stimuli or behavioral ratings, in fMRI) separately, and the predictive map of a model integrates information deriving from both neural activity patterns and experimental design. Not accounting explicitly for the presence of other targets whose associated activity spatially overlaps with the one of interest may lead to predictive maps of troublesome interpretation. We propose a new model that can correctly identify the spatial patterns associated with a target while achieving good generalization. For each target, the training is based on an augmented dataset, which includes all remaining targets. The estimation on such datasets produces both maps and interaction coefficients, which are then used to generalize. The proposed formulation is independent of the regression algorithm employed. We validate this model on simulated fMRI data and on a publicly available dataset. Results indicate that our method achieves high spatial sensitivity and good generalization and that it helps disentangle specific neural effects from interaction with predictive maps associated with other targets. Copyright © 2013 Wiley Periodicals, Inc.

  5. Multivariate Multiple Regression Models for a Big Data-Empowered SON Framework in Mobile Wireless Networks

    Directory of Open Access Journals (Sweden)

    Yoonsu Shin

    2016-01-01

    Full Text Available In the 5G era, the operational cost of mobile wireless networks will significantly increase. Further, massive network capacity and zero latency will be needed because everything will be connected to mobile networks. Thus, self-organizing networks (SON are needed, which expedite automatic operation of mobile wireless networks, but have challenges to satisfy the 5G requirements. Therefore, researchers have proposed a framework to empower SON using big data. The recent framework of a big data-empowered SON analyzes the relationship between key performance indicators (KPIs and related network parameters (NPs using machine-learning tools, and it develops regression models using a Gaussian process with those parameters. The problem, however, is that the methods of finding the NPs related to the KPIs differ individually. Moreover, the Gaussian process regression model cannot determine the relationship between a KPI and its various related NPs. In this paper, to solve these problems, we proposed multivariate multiple regression models to determine the relationship between various KPIs and NPs. If we assume one KPI and multiple NPs as one set, the proposed models help us process multiple sets at one time. Also, we can find out whether some KPIs are conflicting or not. We implement the proposed models using MapReduce.

  6. Non-proportional odds multivariate logistic regression of ordinal family data.

    Science.gov (United States)

    Zaloumis, Sophie G; Scurrah, Katrina J; Harrap, Stephen B; Ellis, Justine A; Gurrin, Lyle C

    2015-03-01

    Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. On the degrees of freedom of reduced-rank estimators in multivariate regression.

    Science.gov (United States)

    Mukherjee, A; Chen, K; Wang, N; Zhu, J

    We study the effective degrees of freedom of a general class of reduced-rank estimators for multivariate regression in the framework of Stein's unbiased risk estimation. A finite-sample exact unbiased estimator is derived that admits a closed-form expression in terms of the thresholded singular values of the least-squares solution and hence is readily computable. The results continue to hold in the high-dimensional setting where both the predictor and the response dimensions may be larger than the sample size. The derived analytical form facilitates the investigation of theoretical properties and provides new insights into the empirical behaviour of the degrees of freedom. In particular, we examine the differences and connections between the proposed estimator and a commonly-used naive estimator. The use of the proposed estimator leads to efficient and accurate prediction risk estimation and model selection, as demonstrated by simulation studies and a data example.

  8. Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

    Science.gov (United States)

    Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

    2017-01-01

    The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

  9. Endpoint in plasma etch process using new modified w-multivariate charts and windowed regression

    Science.gov (United States)

    Zakour, Sihem Ben; Taleb, Hassen

    2017-09-01

    Endpoint detection is very important undertaking on the side of getting a good understanding and figuring out if a plasma etching process is done in the right way, especially if the etched area is very small (0.1%). It truly is a crucial part of supplying repeatable effects in every single wafer. When the film being etched has been completely cleared, the endpoint is reached. To ensure the desired device performance on the produced integrated circuit, the high optical emission spectroscopy (OES) sensor is employed. The huge number of gathered wavelengths (profiles) is then analyzed and pre-processed using a new proposed simple algorithm named Spectra peak selection (SPS) to select the important wavelengths, then we employ wavelet analysis (WA) to enhance the performance of detection by suppressing noise and redundant information. The selected and treated OES wavelengths are then used in modified multivariate control charts (MEWMA and Hotelling) for three statistics (mean, SD and CV) and windowed polynomial regression for mean. The employ of three aforementioned statistics is motivated by controlling mean shift, variance shift and their ratio (CV) if both mean and SD are not stable. The control charts show their performance in detecting endpoint especially W-mean Hotelling chart and the worst result is given by CV statistic. As the best detection of endpoint is given by the W-Hotelling mean statistic, this statistic will be used to construct a windowed wavelet Hotelling polynomial regression. This latter can only identify the window containing endpoint phenomenon.

  10. Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

    Science.gov (United States)

    Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

    2018-03-01

    Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

  11. Multivariate regression analysis for determining short-term values of radon and its decay products from filter measurements

    International Nuclear Information System (INIS)

    Kraut, W.; Schwarz, W.; Wilhelm, A.

    1994-01-01

    A multivariate regression analysis is applied to decay measurements of α-resp. β-filter activcity. Activity concentrations for Po-218, Pb-214 and Bi-214, resp. for the Rn-222 equilibrium equivalent concentration are obtained explicitly. The regression analysis takes into account properly the variances of the measured count rates and their influence on the resulting activity concentrations. (orig.) [de

  12. Regional trends in short-duration precipitation extremes: a flexible multivariate monotone quantile regression approach

    Science.gov (United States)

    Cannon, Alex

    2017-04-01

    univariate technique, and cannot incorporate information from additional covariates, for example ENSO state or physiographic controls on extreme rainfall within a region. Here, the univariate MQR model is extended to allow the use of multiple covariates. Multivariate monotone quantile regression (MMQR) is based on a single hidden-layer feedforward network with the quantile regression error function and partial monotonicity constraints. The MMQR model is demonstrated via Monte Carlo simulations and the estimation and visualization of regional trends in moderate rainfall extremes based on homogenized sub-daily precipitation data at stations in Canada.

  13. Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

    Science.gov (United States)

    Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

    2010-08-01

    The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

  14. Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

    Science.gov (United States)

    Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

    2017-04-01

    Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP

  15. Reporting quality of multivariable logistic regression in selected Indian medical journals.

    Science.gov (United States)

    Kumar, R; Indrayan, A; Chhabra, P

    2012-01-01

    Use of multivariable logistic regression (MLR) modeling has steeply increased in the medical literature over the past few years. Testing of model assumptions and adequate reporting of MLR allow the reader to interpret results more accurately. To review the fulfillment of assumptions and reporting quality of MLR in selected Indian medical journals using established criteria. Analysis of published literature. Medknow.com publishes 68 Indian medical journals with open access. Eight of these journals had at least five articles using MLR between the years 1994 to 2008. Articles from each of these journals were evaluated according to the previously established 10-point quality criteria for reporting and to test the MLR model assumptions. SPSS 17 software and non-parametric test (Kruskal-Wallis H, Mann Whitney U, Spearman Correlation). One hundred and nine articles were finally found using MLR for analyzing the data in the selected eight journals. The number of such articles gradually increased after year 2003, but quality score remained almost similar over time. P value, odds ratio, and 95% confidence interval for coefficients in MLR was reported in 75.2% and sufficient cases (>10) per covariate of limiting sample size were reported in the 58.7% of the articles. No article reported the test for conformity of linear gradient for continuous covariates. Total score was not significantly different across the journals. However, involvement of statistician or epidemiologist as a co-author improved the average quality score significantly (P=0.014). Reporting of MLR in many Indian journals is incomplete. Only one article managed to score 8 out of 10 among 109 articles under review. All others scored less. Appropriate guidelines in instructions to authors, and pre-publication review of articles using MLR by a qualified statistician may improve quality of reporting.

  16. Using Multivariate Adaptive Regression Spline and Artificial Neural Network to Simulate Urbanization in Mumbai, India

    Science.gov (United States)

    Ahmadlou, M.; Delavar, M. R.; Tayyebi, A.; Shafizadeh-Moghadam, H.

    2015-12-01

    Land use change (LUC) models used for modelling urban growth are different in structure and performance. Local models divide the data into separate subsets and fit distinct models on each of the subsets. Non-parametric models are data driven and usually do not have a fixed model structure or model structure is unknown before the modelling process. On the other hand, global models perform modelling using all the available data. In addition, parametric models have a fixed structure before the modelling process and they are model driven. Since few studies have compared local non-parametric models with global parametric models, this study compares a local non-parametric model called multivariate adaptive regression spline (MARS), and a global parametric model called artificial neural network (ANN) to simulate urbanization in Mumbai, India. Both models determine the relationship between a dependent variable and multiple independent variables. We used receiver operating characteristic (ROC) to compare the power of the both models for simulating urbanization. Landsat images of 1991 (TM) and 2010 (ETM+) were used for modelling the urbanization process. The drivers considered for urbanization in this area were distance to urban areas, urban density, distance to roads, distance to water, distance to forest, distance to railway, distance to central business district, number of agricultural cells in a 7 by 7 neighbourhoods, and slope in 1991. The results showed that the area under the ROC curve for MARS and ANN was 94.77% and 95.36%, respectively. Thus, ANN performed slightly better than MARS to simulate urban areas in Mumbai, India.

  17. The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

    Science.gov (United States)

    Warton, David I; Thibaut, Loïc; Wang, Yi Alice

    2017-01-01

    Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

  18. Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic.

    Science.gov (United States)

    McArtor, Daniel B; Lubke, Gitta H; Bergeman, C S

    2017-12-01

    Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes. Multivariate distance matrix regression (MDMR) tests the significance of associations of response profile (dis)similarities and a set of predictors using permutation tests. This paper extends MDMR by deriving and empirically validating the asymptotic null distribution of its test statistic, and by proposing an effect size for individual outcome variables, which is shown to recover true associations. These extensions alleviate the computational burden of permutation tests currently used in MDMR and render more informative results, thus making MDMR accessible to new research domains.

  19. Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.

    Science.gov (United States)

    Lehermeier, Christina; Schön, Chris-Carolin; de Los Campos, Gustavo

    2015-09-01

    Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to "correct" for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP. Copyright © 2015 by the Genetics Society of America.

  20. Order Selection for General Expression of Nonlinear Autoregressive Model Based on Multivariate Stepwise Regression

    Science.gov (United States)

    Shi, Jinfei; Zhu, Songqing; Chen, Ruwen

    2017-12-01

    An order selection method based on multiple stepwise regressions is proposed for General Expression of Nonlinear Autoregressive model which converts the model order problem into the variable selection of multiple linear regression equation. The partial autocorrelation function is adopted to define the linear term in GNAR model. The result is set as the initial model, and then the nonlinear terms are introduced gradually. Statistics are chosen to study the improvements of both the new introduced and originally existed variables for the model characteristics, which are adopted to determine the model variables to retain or eliminate. So the optimal model is obtained through data fitting effect measurement or significance test. The simulation and classic time-series data experiment results show that the method proposed is simple, reliable and can be applied to practical engineering.

  1. Dental age assessment of young Iranian adults using third molars: A multivariate regression study.

    Science.gov (United States)

    Bagherpour, Ali; Anbiaee, Najmeh; Partovi, Parnia; Golestani, Shayan; Afzalinasab, Shakiba

    2012-10-01

    In recent years, a noticeable increase in forensic age estimations of living individuals has been observed. Radiologic assessment of the mineralisation stage of third molars is of particular importance, with regard to the relevant age group. To attain a referral database and regression equations for dental age estimation of unaccompanied minors in an Iranian population was the goal of this study. Moreover, determination was made concerning the probability of an individual being over the age of 18 in case of full third molar(s) development. Using the scoring system of Gleiser and Hunt, modified by Köhler, an investigation of a cross-sectional sample of 1274 orthopantomograms of 885 females and 389 males aged between 15 and 22 years was carried out. Using kappa statistics, intra-observer reliability was tested. With Spearman correlation coefficient, correlation between the scores of all four wisdom teeth, was evaluated. We also carried out the Wilcoxon signed-rank test on asymmetry and calculated the regression formulae. A strong intra-observer agreement was displayed by the kappa value. No significant difference (p-value for upper and lower jaws were 0.07 and 0.59, respectively) was discovered by Wilcoxon signed-rank test for left and right asymmetry. The developmental stage of upper right and upper left third molars yielded the greatest correlation coefficient. The probability of an individual being over the age of 18 is 95.6% for males and 100.0% for females in case four fully developed third molars are present. Taking into consideration gender, location and number of wisdom teeth, regression formulae were arrived at. Use of population-specific standards is recommended as a means of improving the accuracy of forensic age estimates based on third molars mineralisation. To obtain more exact regression formulae, wider age range studies are recommended. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

  2. Application of Multivariate Adaptive Regression Splines to Sheet Metal Bending Process for Springback Compensation

    Directory of Open Access Journals (Sweden)

    Dilan Rasim Aşkın

    2016-01-01

    Full Text Available An intelligent regression technique is applied for sheet metal bending processes to improve bending performance. This study is a part of another extensive study, automated sheet bending assistance for press brakes. Data related to material properties of sheet metal is collected in an online manner and fed to an intelligent system for determining the most accurate punch displacement without any offline iteration or calibration. The overall system aims to reduce the production time while increasing the performance of press brakes.

  3. Economic viability in concrete dams by multivariable regression tool for implantation of small hydroelectric plants

    International Nuclear Information System (INIS)

    Lima, Reginaldo Agapito de; Ribeiro Junior, Leopoldo Uberto

    2010-01-01

    For implantation of a SHP, the barrage is the main structure where its sizing represents from 30% - 50% of general cost of civil works. Considering this it is very important to have a fast, didactic and accurate tool for elaborating a budget, also allowing a quantitative analysis of inherent cost for civil building of barrages concrete made for small hydropower plants. In face of this, the multi changing regression tool is very important as it allows a fast and correct establishing of preliminary costs, even approximate, for estimates of barrages in concrete cost, enabling to ease the budget, guiding feasibility decisions for selecting or neglecting new alternatives of fall. (author)

  4. A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

    Science.gov (United States)

    Delwiche, Stephen R; Reeves, James B

    2010-01-01

    In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various

  5. Determination of boiling point of petrochemicals by gas chromatography-mass spectrometry and multivariate regression analysis of structural activity relationship.

    Science.gov (United States)

    Fakayode, Sayo O; Mitchell, Breanna S; Pollard, David A

    2014-08-01

    Accurate understanding of analyte boiling points (BP) is of critical importance in gas chromatographic (GC) separation and crude oil refinery operation in petrochemical industries. This study reported the first combined use of GC separation and partial-least-square (PLS1) multivariate regression analysis of petrochemical structural activity relationship (SAR) for accurate BP determination of two commercially available (D3710 and MA VHP) calibration gas mix samples. The results of the BP determination using PLS1 multivariate regression were further compared with the results of traditional simulated distillation method of BP determination. The developed PLS1 regression was able to correctly predict analytes BP in D3710 and MA VHP calibration gas mix samples, with a root-mean-square-%-relative-error (RMS%RE) of 6.4%, and 10.8% respectively. In contrast, the overall RMS%RE of 32.9% and 40.4%, respectively obtained for BP determination in D3710 and MA VHP using a traditional simulated distillation method were approximately four times larger than the corresponding RMS%RE of BP prediction using MRA, demonstrating the better predictive ability of MRA. The reported method is rapid, robust, and promising, and can be potentially used routinely for fast analysis, pattern recognition, and analyte BP determination in petrochemical industries. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Diagnostic accuracy of atypical p-ANCA in autoimmune hepatitis using ROC- and multivariate regression analysis.

    Science.gov (United States)

    Terjung, B; Bogsch, F; Klein, R; Söhne, J; Reichel, C; Wasmuth, J-C; Beuers, U; Sauerbruch, T; Spengler, U

    2004-09-29

    Antineutrophil cytoplasmic antibodies (atypical p-ANCA) are detected at high prevalence in sera from patients with autoimmune hepatitis (AIH), but their diagnostic relevance for AIH has not been systematically evaluated so far. Here, we studied sera from 357 patients with autoimmune (autoimmune hepatitis n=175, primary sclerosing cholangitis (PSC) n=35, primary biliary cirrhosis n=45), non-autoimmune chronic liver disease (alcoholic liver cirrhosis n=62; chronic hepatitis C virus infection (HCV) n=21) or healthy controls (n=19) for the presence of various non-organ specific autoantibodies. Atypical p-ANCA, antinuclear antibodies (ANA), antibodies against smooth muscles (SMA), antibodies against liver/kidney microsomes (anti-Lkm1) and antimitochondrial antibodies (AMA) were detected by indirect immunofluorescence microscopy, antibodies against the M2 antigen (anti-M2), antibodies against soluble liver antigen (anti-SLA/LP) and anti-Lkm1 by using enzyme linked immunosorbent assays. To define the diagnostic precision of the autoantibodies, results of autoantibody testing were analyzed by receiver operating characteristics (ROC) and forward conditional logistic regression analysis. Atypical p-ANCA were detected at high prevalence in sera from patients with AIH (81%) and PSC (94%). ROC- and logistic regression analysis revealed atypical p-ANCA and SMA, but not ANA as significant diagnostic seromarkers for AIH (atypical p-ANCA: AUC 0.754+/-0.026, odds ratio [OR] 3.4; SMA: 0.652+/-0.028, OR 4.1). Atypical p-ANCA also emerged as the only diagnostically relevant seromarker for PSC (AUC 0.690+/-0.04, OR 3.4). None of the tested antibodies yielded a significant diagnostic accuracy for patients with alcoholic liver cirrhosis, HCV or healthy controls. Atypical p-ANCA along with SMA represent a seromarker with high diagnostic accuracy for AIH and should be explicitly considered in a revised version of the diagnostic score for AIH.

  7. Boosted regression trees, multivariate adaptive regression splines and their two-step combinations with multiple linear regression or partial least squares to predict blood-brain barrier passage: a case study.

    Science.gov (United States)

    Deconinck, E; Zhang, M H; Petitet, F; Dubus, E; Ijjaali, I; Coomans, D; Vander Heyden, Y

    2008-02-18

    The use of some unconventional non-linear modeling techniques, i.e. classification and regression trees and multivariate adaptive regression splines-based methods, was explored to model the blood-brain barrier (BBB) passage of drugs and drug-like molecules. The data set contains BBB passage values for 299 structural and pharmacological diverse drugs, originating from a structured knowledge-based database. Models were built using boosted regression trees (BRT) and multivariate adaptive regression splines (MARS), as well as their respective combinations with stepwise multiple linear regression (MLR) and partial least squares (PLS) regression in two-step approaches. The best models were obtained using combinations of MARS with either stepwise MLR or PLS. It could be concluded that the use of combinations of a linear with a non-linear modeling technique results in some improved properties compared to the individual linear and non-linear models and that, when the use of such a combination is appropriate, combinations using MARS as non-linear technique should be preferred over those with BRT, due to some serious drawbacks of the BRT approaches.

  8. Multivariate regression applied to the performance optimization of a countercurrent ultracentrifuge - a preliminary study

    International Nuclear Information System (INIS)

    Migliavacca, Elder; Andrade, Delvonei Alves de

    2004-01-01

    In this work, the least-squares methodology with covariance matrix is applied to determine a data curve fitting in order to obtain a performance function for the separative power δU of a ultracentrifuge as a function of variables that are experimentally controlled. The experimental data refer to 173 experiments on the ultracentrifugation process for uranium isotope separation. The experimental uncertainties related with these independent variables are considered in the calculation of the experimental separative power values, determining an experimental data input covariance matrix. The process control variables, which significantly influence the δU values, are chosen in order to give information on the ultracentrifuge behaviour when submitted to several levels of feed flow F and cut θ . After the model goodness-of-fit validation, a residual analysis is carried out to verify the assumed basis concerning its randomness and independence and mainly the existence of residual heterocedasticity with any regression model variable. The response curves are made relating the separative power with the control variables F and θ, to compare the fitted model with the experimental data and finally to calculate their optimized values. (author)

  9. Prediction of diffuse solar irradiance using machine learning and multivariable regression

    International Nuclear Information System (INIS)

    Lou, Siwei; Li, Danny H.W.; Lam, Joseph C.; Chan, Wilco W.H.

    2016-01-01

    Highlights: • 54.9% of the annual global irradiance is composed by its diffuse part in HK. • Hourly diffuse irradiance was predicted by accessible variables. • The importance of variable in prediction was assessed by machine learning. • Simple prediction equations were developed with the knowledge of variable importance. - Abstract: The paper studies the horizontal global, direct-beam and sky-diffuse solar irradiance data measured in Hong Kong from 2008 to 2013. A machine learning algorithm was employed to predict the horizontal sky-diffuse irradiance and conduct sensitivity analysis for the meteorological variables. Apart from the clearness index (horizontal global/extra atmospheric solar irradiance), we found that predictors including solar altitude, air temperature, cloud cover and visibility are also important in predicting the diffuse component. The mean absolute error (MAE) of the logistic regression using the aforementioned predictors was less than 21.5 W/m"2 and 30 W/m"2 for Hong Kong and Denver, USA, respectively. With the systematic recording of the five variables for more than 35 years, the proposed model would be appropriate to estimate of long-term diffuse solar radiation, study climate change and develope typical meteorological year in Hong Kong and places with similar climates.

  10. Multivariate Regression Analysis and Statistical Modeling for Summer Extreme Precipitation over the Yangtze River Basin, China

    Directory of Open Access Journals (Sweden)

    Tao Gao

    2014-01-01

    Full Text Available Extreme precipitation is likely to be one of the most severe meteorological disasters in China; however, studies on the physical factors affecting precipitation extremes and corresponding prediction models are not accurately available. From a new point of view, the sensible heat flux (SHF and latent heat flux (LHF, which have significant impacts on summer extreme rainfall in Yangtze River basin (YRB, have been quantified and then selections of the impact factors are conducted. Firstly, a regional extreme precipitation index was applied to determine Regions of Significant Correlation (RSC by analyzing spatial distribution of correlation coefficients between this index and SHF, LHF, and sea surface temperature (SST on global ocean scale; then the time series of SHF, LHF, and SST in RSCs during 1967–2010 were selected. Furthermore, other factors that significantly affect variations in precipitation extremes over YRB were also selected. The methods of multiple stepwise regression and leave-one-out cross-validation (LOOCV were utilized to analyze and test influencing factors and statistical prediction model. The correlation coefficient between observed regional extreme index and model simulation result is 0.85, with significant level at 99%. This suggested that the forecast skill was acceptable although many aspects of the prediction model should be improved.

  11. Multivariate regression models for the simultaneous quantitative analysis of calcium and magnesium carbonates and magnesium oxide through drifts data

    Directory of Open Access Journals (Sweden)

    Marder Luciano

    2006-01-01

    Full Text Available In the present work multivariate regression models were developed for the quantitative analysis of ternary systems using Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS to determine the concentration in weight of calcium carbonate, magnesium carbonate and magnesium oxide. Nineteen spectra of standard samples previously defined in ternary diagram by mixture design were prepared and mid-infrared diffuse reflectance spectra were recorded. The partial least squares (PLS regression method was applied to the model. The spectra set was preprocessed by either mean-centered and variance-scaled (model 2 or mean-centered only (model 1. The results based on the prediction performance of the external validation set expressed by RMSEP (root mean square error of prediction demonstrated that it is possible to develop good models to simultaneously determine calcium carbonate, magnesium carbonate and magnesium oxide content in powdered samples that can be used in the study of the thermal decomposition of dolomite rocks.

  12. Perioperative factors predicting poor outcome in elderly patients following emergency general surgery: a multivariate regression analysis

    Science.gov (United States)

    Lees, Mackenzie C.; Merani, Shaheed; Tauh, Keerit; Khadaroo, Rachel G.

    2015-01-01

    Background Older adults (≥ 65 yr) are the fastest growing population and are presenting in increasing numbers for acute surgical care. Emergency surgery is frequently life threatening for older patients. Our objective was to identify predictors of mortality and poor outcome among elderly patients undergoing emergency general surgery. Methods We conducted a retrospective cohort study of patients aged 65–80 years undergoing emergency general surgery between 2009 and 2010 at a tertiary care centre. Demographics, comorbidities, in-hospital complications, mortality and disposition characteristics of patients were collected. Logistic regression analysis was used to identify covariate-adjusted predictors of in-hospital mortality and discharge of patients home. Results Our analysis included 257 patients with a mean age of 72 years; 52% were men. In-hospital mortality was 12%. Mortality was associated with patients who had higher American Society of Anesthesiologists (ASA) class (odds ratio [OR] 3.85, 95% confidence interval [CI] 1.43–10.33, p = 0.008) and in-hospital complications (OR 1.93, 95% CI 1.32–2.83, p = 0.001). Nearly two-thirds of patients discharged home were younger (OR 0.92, 95% CI 0.85–0.99, p = 0.036), had lower ASA class (OR 0.45, 95% CI 0.27–0.74, p = 0.002) and fewer in-hospital complications (OR 0.69, 95% CI 0.53–0.90, p = 0.007). Conclusion American Society of Anesthesiologists class and in-hospital complications are perioperative predictors of mortality and disposition in the older surgical population. Understanding the predictors of poor outcome and the importance of preventing in-hospital complications in older patients will have important clinical utility in terms of preoperative counselling, improving health care and discharging patients home. PMID:26204143

  13. Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines

    International Nuclear Information System (INIS)

    Li, Yanting; He, Yong; Su, Yan; Shu, Lianjie

    2016-01-01

    Highlights: • Suggests a nonparametric model based on MARS for output power prediction. • Compare the MARS model with a wide variety of prediction models. • Show that the MARS model is able to provide an overall good performance in both the training and testing stages. - Abstract: Both linear and nonlinear models have been proposed for forecasting the power output of photovoltaic systems. Linear models are simple to implement but less flexible. Due to the stochastic nature of the power output of PV systems, nonlinear models tend to provide better forecast than linear models. Motivated by this, this paper suggests a fairly simple nonlinear regression model known as multivariate adaptive regression splines (MARS), as an alternative to forecasting of solar power output. The MARS model is a data-driven modeling approach without any assumption about the relationship between the power output and predictors. It maintains simplicity of the classical multiple linear regression (MLR) model while possessing the capability of handling nonlinearity. It is simpler in format than other nonlinear models such as ANN, k-nearest neighbors (KNN), classification and regression tree (CART), and support vector machine (SVM). The MARS model was applied on the daily output of a grid-connected 2.1 kW PV system to provide the 1-day-ahead mean daily forecast of the power output. The comparisons with a wide variety of forecast models show that the MARS model is able to provide reliable forecast performance.

  14. [Multivariate ordinal logistic regression analysis on the association between consumption of fried food and both esophageal cancer and precancerous lesions].

    Science.gov (United States)

    Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

    2017-12-10

    Objective: To investigate the effect of fried food intake on the pathogenesis of esophageal cancer and precancerous lesions. Methods: From 2005 to 2013, all the residents aged 40-69 years from 11 counties (cities) where cancer screening of upper gastrointestinal cancer had been conducted in rural areas of Henan province, were recruited as the subjects of study. Information on demography and lifestyle was collected. The residents under study were screened with iodine staining endoscopic examination and biopsy samples were diagnosed pathologically, under standardized criteria. Subjects with high risk were divided into the groups based on their different pathological degrees. Multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and esophageal cancer and precancerous lesions. Results: A total number of 8 792 cases with normal esophagus, 3 680 with mild hyperplasia, 972 with moderate hyperplasia, 413 with severe hyperplasia carcinoma in situ, and 336 cases of esophageal cancer were recruited. Results from multivariate logistic regression analysis showed that, when compared with those who did not eat fried food, the intake of fried food (food appeared a risk factor for both esophageal cancer and precancerous lesions.

  15. Application of multivariate adaptive regression spine-assisted objective function on optimization of heat transfer rate around a cylinder

    Energy Technology Data Exchange (ETDEWEB)

    Dey, Prasenjit; Dad, Ajoy K. [Mechanical Engineering Department, National Institute of Technology, Agartala (India)

    2016-12-15

    The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015). Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

  16. Research on refugees and immigrants social integration in Yunnan Border Area: An empirical analysis on the multivariable linear regression model

    Directory of Open Access Journals (Sweden)

    Peng Nai

    2016-03-01

    Full Text Available A great number of immigration populations resident permanently in Yunnan Border Area of China. To some extent, these people belong to refugees or immigrants in accordance with International Rules, which significantly features the social diversity of this area. However, this kind of social diversity always impairs the social order. Therefore, there will be a positive influence to the local society governance by a research on local immigration integration. This essay hereby attempts to acquire the data of the living situation of these border area immigration and refugees. The analysis of the social integration of refugees and immigration in Yunnan border area in China will be deployed through the modeling of multivariable linear regression based on these data in order to propose some more achievable resolutions.

  17. Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

    Science.gov (United States)

    Hasyim, M.; Prastyo, D. D.

    2018-03-01

    Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

  18. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  19. Geoelectrical parameter-based multivariate regression borehole yield model for predicting aquifer yield in managing groundwater resource sustainability

    Directory of Open Access Journals (Sweden)

    Kehinde Anthony Mogaji

    2016-07-01

    Full Text Available This study developed a GIS-based multivariate regression (MVR yield rate prediction model of groundwater resource sustainability in the hard-rock geology terrain of southwestern Nigeria. This model can economically manage the aquifer yield rate potential predictions that are often overlooked in groundwater resources development. The proposed model relates the borehole yield rate inventory of the area to geoelectrically derived parameters. Three sets of borehole yield rate conditioning geoelectrically derived parameters—aquifer unit resistivity (ρ, aquifer unit thickness (D and coefficient of anisotropy (λ—were determined from the acquired and interpreted geophysical data. The extracted borehole yield rate values and the geoelectrically derived parameter values were regressed to develop the MVR relationship model by applying linear regression and GIS techniques. The sensitivity analysis results of the MVR model evaluated at P ⩽ 0.05 for the predictors ρ, D and λ provided values of 2.68 × 10−05, 2 × 10−02 and 2.09 × 10−06, respectively. The accuracy and predictive power tests conducted on the MVR model using the Theil inequality coefficient measurement approach, coupled with the sensitivity analysis results, confirmed the model yield rate estimation and prediction capability. The MVR borehole yield prediction model estimates were processed in a GIS environment to model an aquifer yield potential prediction map of the area. The information on the prediction map can serve as a scientific basis for predicting aquifer yield potential rates relevant in groundwater resources sustainability management. The developed MVR borehole yield rate prediction mode provides a good alternative to other methods used for this purpose.

  20. Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy)

    Science.gov (United States)

    Conoscenti, Christian; Ciaccio, Marilena; Caraballo-Arias, Nathalie Almaru; Gómez-Gutiérrez, Álvaro; Rotigliano, Edoardo; Agnesi, Valerio

    2015-08-01

    In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km2. To explore the effect of pre-failure topography on earth-flow spatial distribution, we performed a reconstruction of topography before the landslide occurrence. This was achieved by preparing a digital terrain model (DTM) where altitude of areas hosting landslides was interpolated from the adjacent undisturbed land surface by using the algorithm topo-to-raster. This DTM was exploited to extract 15 morphological and hydrological variables that, in addition to outcropping lithology, were employed as explanatory variables of earth-flow spatial distribution. The predictive skill of the earth-flow susceptibility models and the robustness of the procedure were tested by preparing five datasets, each including a different subset of landslides and stable areas. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The results demonstrate that the overall accuracy of LR and MARS earth-flow susceptibility models is from excellent to outstanding. However, AUC values of the validation datasets attest to a higher predictive power of MARS-models (AUC between 0.881 and 0.912) with respect to LR-models (AUC between 0.823 and 0.870). The adopted procedure proved to be resistant to overfitting and stable when changes of the learning and validation samples are

  1. Trochanteric entry femoral nails yield better femoral version and lower revision rates-A large cohort multivariate regression analysis.

    Science.gov (United States)

    Yoon, Richard S; Gage, Mark J; Galos, David K; Donegan, Derek J; Liporace, Frank A

    2017-06-01

    Intramedullary nailing (IMN) has become the standard of care for the treatment of most femoral shaft fractures. Different IMN options include trochanteric and piriformis entry as well as retrograde nails, which may result in varying degrees of femoral rotation. The objective of this study was to analyze postoperative femoral version between three types of nails and to delineate any significant differences in femoral version (DFV) and revision rates. Over a 10-year period, 417 patients underwent IMN of a diaphyseal femur fracture (AO/OTA 32A-C). Of these patients, 316 met inclusion criteria and obtained postoperative computed tomography (CT) scanograms to calculate femoral version and were thus included in the study. In this study, our main outcome measure was the difference in femoral version (DFV) between the uninjured limb and the injured limb. The effect of the following variables on DFV and revision rates were determined via univariate, multivariate, and ordinal regression analyses: gender, age, BMI, ethnicity, mechanism of injury, operative side, open fracture, and table type/position. Statistical significance was set at pregression analysis revealed that a lower BMI was significantly associated with a lower DFV (p=0.006). Controlling for possible covariables, multivariate analysis yielded a significantly lower DFV for trochanteric entry nails than piriformis or retrograde nails (7.9±6.10 vs. 9.5±7.4 vs. 9.4±7.8°, pregression analysis. However, this is not to state that the other nail types exhibited abnormal DFV. Translation to the clinical impact of a few degrees of DFV is also unknown. Future studies to more in-depth study the intricacies of femoral version may lead to improved technology in addition to potentially improved clinical outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. A retrospective study: Multivariate logistic regression analysis of the outcomes after pressure sores reconstruction with fasciocutaneous, myocutaneous, and perforator flaps.

    Science.gov (United States)

    Chiu, Yu-Jen; Liao, Wen-Chieh; Wang, Tien-Hsiang; Shih, Yu-Chung; Ma, Hsu; Lin, Chih-Hsun; Wu, Szu-Hsien; Perng, Cherng-Kang

    2017-08-01

    Despite significant advances in medical care and surgical techniques, pressure sore reconstruction is still prone to elevated rates of complication and recurrence. We conducted a retrospective study to investigate not only complication and recurrence rates following pressure sore reconstruction but also preoperative risk stratification. This study included 181 ulcers underwent flap operations between January 2002 and December 2013 were included in the study. We performed a multivariable logistic regression model, which offers a regression-based method accounting for the within-patient correlation of the success or failure of each flap. The overall complication and recurrence rates for all flaps were 46.4% and 16.0%, respectively, with a mean follow-up period of 55.4 ± 38.0 months. No statistically significant differences of complication and recurrence rates were observed among three different reconstruction methods. In subsequent analysis, albumin ≤3.0 g/dl and paraplegia were significantly associated with higher postoperative complication. The anatomic factor, ischial wound location, significantly trended toward the development of ulcer recurrence. In the fasciocutaneous group, paraplegia had significant correlation to higher complication and recurrence rates. In the musculocutaneous flap group, variables had no significant correlation to complication and recurrence rates. In the free-style perforator group, ischial wound location and malnourished status correlated with significantly higher complication rates; ischial wound location also correlated with significantly higher recurrence rate. Ultimately, our review of a noteworthy cohort with lengthy follow-up helped identify and confirm certain risk factors that can facilitate a more informed and thoughtful pre- and postoperative decision-making process for patients with pressure ulcers. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All

  3. Using multiobjective tradeoff sets and Multivariate Regression Trees to identify critical and robust decisions for long term water utility planning

    Science.gov (United States)

    Smith, R.; Kasprzyk, J. R.; Balaji, R.

    2017-12-01

    In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.

  4. A Model for Shovel Capital Cost Estimation, Using a Hybrid Model of Multivariate Regression and Neural Networks

    Directory of Open Access Journals (Sweden)

    Abdolreza Yazdani-Chamzini

    2017-12-01

    Full Text Available Cost estimation is an essential issue in feasibility studies in civil engineering. Many different methods can be applied to modelling costs. These methods can be divided into several main groups: (1 artificial intelligence, (2 statistical methods, and (3 analytical methods. In this paper, the multivariate regression (MVR method, which is one of the most popular linear models, and the artificial neural network (ANN method, which is widely applied to solving different prediction problems with a high degree of accuracy, have been combined to provide a cost estimate model for a shovel machine. This hybrid methodology is proposed, taking the advantages of MVR and ANN models in linear and nonlinear modelling, respectively. In the proposed model, the unique advantages of the MVR model in linear modelling are used first to recognize the existing linear structure in data, and, then, the ANN for determining nonlinear patterns in preprocessed data is applied. The results with three indices indicate that the proposed model is efficient and capable of increasing the prediction accuracy.

  5. Multivariate Adaptative Regression Splines (MARS, una alternativa para el análisis de series de tiempo

    Directory of Open Access Journals (Sweden)

    Jairo Vanegas

    2017-05-01

    Full Text Available Multivariate Adaptative Regression Splines (MARS es un método de modelación no paramétrico que extiende el modelo lineal incorporando no linealidades e interacciones de variables. Es una herramienta flexible que automatiza la construcción de modelos de predicción, seleccionando variables relevantes, transformando las variables predictoras, tratando valores perdidos y previniendo sobreajustes mediante un autotest. También permite predecir tomando en cuenta factores estructurales que pudieran tener influencia sobre la variable respuesta, generando modelos hipotéticos. El resultado final serviría para identificar puntos de corte relevantes en series de datos. En el área de la salud es poco utilizado, por lo que se propone como una herramienta más para la evaluación de indicadores relevantes en salud pública. Para efectos demostrativos se utilizaron series de datos de mortalidad de menores de 5 años de Costa Rica en el periodo 1978-2008.

  6. Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree

    Science.gov (United States)

    Heddam, Salim; Kisi, Ozgur

    2018-04-01

    In the present study, three types of artificial intelligence techniques, least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5T) are applied for modeling daily dissolved oxygen (DO) concentration using several water quality variables as inputs. The DO concentration and water quality variables data from three stations operated by the United States Geological Survey (USGS) were used for developing the three models. The water quality data selected consisted of daily measured of water temperature (TE, °C), pH (std. unit), specific conductance (SC, μS/cm) and discharge (DI cfs), are used as inputs to the LSSVM, MARS and M5T models. The three models were applied for each station separately and compared to each other. According to the results obtained, it was found that: (i) the DO concentration could be successfully estimated using the three models and (ii) the best model among all others differs from one station to another.

  7. Is ovarian hyperstimulation associated with higher blood pressure in 4-year-old IVF offspring? Part I: multivariable regression analysis.

    Science.gov (United States)

    Seggers, Jorien; Haadsma, Maaike L; La Bastide-Van Gemert, Sacha; Heineman, Maas Jan; Middelburg, Karin J; Roseboom, Tessa J; Schendelaar, Pamela; Van den Heuvel, Edwin R; Hadders-Algra, Mijna

    2014-03-01

    Does ovarian hyperstimulation, the in vitro procedure, or a combination of these two negatively influence blood pressure (BP) and anthropometrics of 4-year-old children born following IVF? Higher systolic blood pressure (SBP) percentiles were found in 4-year-old children born following conventional IVF with ovarian hyperstimulation compared with children born following IVF without ovarian hyperstimulation. Increasing evidence suggests that IVF, which has an increased incidence of preterm birth and low birthweight, is associated with higher BP and altered body fat distribution in offspring but the underlying mechanisms are largely unknown. We performed a prospective, assessor-blinded follow-up study in which 194 children were assessed. The attrition rate up until the 4-year-old assessment was 10%. We measured BP and anthropometrics of 4-year-old singletons born following conventional IVF with controlled ovarian hyperstimulation (COH-IVF, n = 63), or born following modified natural cycle IV (MNC-IVF, n = 52), or born to subfertile couples who conceived naturally (Sub-NC, n = 79). Both IVF and ICSI were performed. Primary outcome measures were the SBP percentiles and diastolic BP (DBP) percentiles. Anthropometric measures included triceps and subscapular skinfold thickness. Several multivariable regression analyses were applied in order to correct for subsets of confounders. The value 'B' is the unstandardized regression coefficient. SBP percentiles were significantly lower in the MNC-IVF group (mean 59, SD 24) than in the COH-IVF (mean 68, SD 22) and Sub-NC groups (mean 70, SD 16). The difference in SBP between COH-IVF and MNC-IVF remained significant after correction for current, early life and parental characteristics (B: 14.09; 95% confidence interval (CI): 5.39-22.79), whereas the difference between MNC-IVF and Sub-NC did not. DBP percentiles did not differ between groups. After correction for early life factors, subscapular skinfold thickness was thicker in the

  8. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  9. Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

    Science.gov (United States)

    Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

    2018-03-01

    This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

  10. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    Science.gov (United States)

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  11. Multispectral colormapping using penalized least square regression

    DEFF Research Database (Denmark)

    Dissing, Bjørn Skovlund; Carstensen, Jens Michael; Larsen, Rasmus

    2010-01-01

    The authors propose a novel method to map a multispectral image into the device independent color space CIE-XYZ. This method provides a way to visualize multispectral images by predicting colorvalues from spectral values while maintaining interpretability and is tested on a light emitting diode...... that the interpretability improves significantly but comes at the cost of slightly worse predictability....

  12. Poverty Control and the Penal System

    Directory of Open Access Journals (Sweden)

    Fernanda Kilduff

    2010-01-01

    Full Text Available To reflect on the criminalization and penalization of poverty, this article analyzes the neoconservative turn in criminal policy, as an expression of recent changes under contemporary capitalism. In a context characterized by a regression in social policies, the paper discusses the expansion of the penal system as a strategy used by capitalist States to contain and administer in a criminalizing form the growing and increasingly complex manifestations of the “social question” linked to an objective situation of massive and structural unemployment. To conclude the debate, it presents some elements to reflect on the historic function of bourgeois penal law and to analyze its fundamental role in current imperialist strategy.

  13. Effects of univariate and multivariate regression on the accuracy of hydrogen quantification with laser-induced breakdown spectroscopy

    Science.gov (United States)

    Ytsma, Cai R.; Dyar, M. Darby

    2018-01-01

    Hydrogen (H) is a critical element to measure on the surface of Mars because its presence in mineral structures is indicative of past hydrous conditions. The Curiosity rover uses the laser-induced breakdown spectrometer (LIBS) on the ChemCam instrument to analyze rocks for their H emission signal at 656.6 nm, from which H can be quantified. Previous LIBS calibrations for H used small data sets measured on standards and/or manufactured mixtures of hydrous minerals and rocks and applied univariate regression to spectra normalized in a variety of ways. However, matrix effects common to LIBS make these calibrations of limited usefulness when applied to the broad range of compositions on the Martian surface. In this study, 198 naturally-occurring hydrous geological samples covering a broad range of bulk compositions with directly-measured H content are used to create more robust prediction models for measuring H in LIBS data acquired under Mars conditions. Both univariate and multivariate prediction models, including partial least square (PLS) and the least absolute shrinkage and selection operator (Lasso), are compared using several different methods for normalization of H peak intensities. Data from the ChemLIBS Mars-analog spectrometer at Mount Holyoke College are compared against spectra from the same samples acquired using a ChemCam-like instrument at Los Alamos National Laboratory and the ChemCam instrument on Mars. Results show that all current normalization and data preprocessing variations for quantifying H result in models with statistically indistinguishable prediction errors (accuracies) ca. ± 1.5 weight percent (wt%) H2O, limiting the applications of LIBS in these implementations for geological studies. This error is too large to allow distinctions among the most common hydrous phases (basalts, amphiboles, micas) to be made, though some clays (e.g., chlorites with ≈ 12 wt% H2O, smectites with 15-20 wt% H2O) and hydrated phases (e.g., gypsum with ≈ 20

  14. Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

    Science.gov (United States)

    Michael S. Balshi; A. David McGuire; Paul Duffy; Mike Flannigan; John Walsh; Jerry Melillo

    2009-01-01

    We developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5o (latitude x longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was...

  15. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study

    Directory of Open Access Journals (Sweden)

    Tania Dehesh

    2015-01-01

    Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

  16. The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

    Science.gov (United States)

    Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

    2015-01-01

    Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

  17. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

    Science.gov (United States)

    Pradhan, Biswajeet

    2010-05-01

    This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross

  18. Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

    Science.gov (United States)

    Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

    2017-05-01

    The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for

  19. An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

    Science.gov (United States)

    Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

  20. An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

    Science.gov (United States)

    Smith, Kelly; Gay, Robert; Stachowiak, Susan

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

  1. New strategy for determination of anthocyanins, polyphenols and antioxidant capacity of Brassica oleracea liquid extract using infrared spectroscopies and multivariate regression

    Science.gov (United States)

    de Oliveira, Isadora R. N.; Roque, Jussara V.; Maia, Mariza P.; Stringheta, Paulo C.; Teófilo, Reinaldo F.

    2018-04-01

    A new method was developed to determine the antioxidant properties of red cabbage extract (Brassica oleracea) by mid (MID) and near (NIR) infrared spectroscopies and partial least squares (PLS) regression. A 70% (v/v) ethanolic extract of red cabbage was concentrated to 9° Brix and further diluted (12 to 100%) in water. The dilutions were used as external standards for the building of PLS models. For the first time, this strategy was applied for building multivariate regression models. Reference analyses and spectral data were obtained from diluted extracts. The determinate properties were total and monomeric anthocyanins, total polyphenols and antioxidant capacity by ABTS (2,2-azino-bis(3-ethyl-benzothiazoline-6-sulfonate)) and DPPH (2,2-diphenyl-1-picrylhydrazyl) methods. Ordered predictors selection (OPS) and genetic algorithm (GA) were used for feature selection before PLS regression (PLS-1). In addition, a PLS-2 regression was applied to all properties simultaneously. PLS-1 models provided more predictive models than did PLS-2 regression. PLS-OPS and PLS-GA models presented excellent prediction results with a correlation coefficient higher than 0.98. However, the best models were obtained using PLS and variable selection with the OPS algorithm and the models based on NIR spectra were considered more predictive for all properties. Then, these models provided a simple, rapid and accurate method for determination of red cabbage extract antioxidant properties and its suitability for use in the food industry.

  2. Partitioning of Multivariate Phenotypes using Regression Trees Reveals Complex Patterns of Adaptation to Climate across the Range of Black Cottonwood (Populus trichocarpa

    Directory of Open Access Journals (Sweden)

    Regis Wendpouire Oubida

    2015-03-01

    Full Text Available Local adaptation to climate in temperate forest trees involves the integration of multiple physiological, morphological, and phenological traits. Latitudinal clines are frequently observed for these traits, but environmental constraints also track longitude and altitude. We combined extensive phenotyping of 12 candidate adaptive traits, multivariate regression trees, quantitative genetics, and a genome-wide panel of SNP markers to better understand the interplay among geography, climate, and adaptation to abiotic factors in Populus trichocarpa. Heritabilities were low to moderate (0.13 to 0.32 and population differentiation for many traits exceeded the 99th percentile of the genome-wide distribution of FST, suggesting local adaptation. When climate variables were taken as predictors and the 12 traits as response variables in a multivariate regression tree analysis, evapotranspiration (Eref explained the most variation, with subsequent splits related to mean temperature of the warmest month, frost-free period (FFP, and mean annual precipitation (MAP. These grouping matched relatively well the splits using geographic variables as predictors: the northernmost groups (short FFP and low Eref had the lowest growth, and lowest cold injury index; the southern British Columbia group (low Eref and intermediate temperatures had average growth and cold injury index; the group from the coast of California and Oregon (high Eref and FFP had the highest growth performance and the highest cold injury index; and the southernmost, high-altitude group (with high Eref and low FFP performed poorly, had high cold injury index, and lower water use efficiency. Taken together, these results suggest variation in both temperature and water availability across the range shape multivariate adaptive traits in poplar.

  3. Simultaneous determination of estrogens (ethinylestradiol and norgestimate) concentrations in human and bovine serum albumin by use of fluorescence spectroscopy and multivariate regression analysis.

    Science.gov (United States)

    Hordge, LaQuana N; McDaniel, Kiara L; Jones, Derick D; Fakayode, Sayo O

    2016-05-15

    The endocrine disruption property of estrogens necessitates the immediate need for effective monitoring and development of analytical protocols for their analyses in biological and human specimens. This study explores the first combined utility of a steady-state fluorescence spectroscopy and multivariate partial-least-square (PLS) regression analysis for the simultaneous determination of two estrogens (17α-ethinylestradiol (EE) and norgestimate (NOR)) concentrations in bovine serum albumin (BSA) and human serum albumin (HSA) samples. The influence of EE and NOR concentrations and temperature on the emission spectra of EE-HSA EE-BSA, NOR-HSA, and NOR-BSA complexes was also investigated. The binding of EE with HSA and BSA resulted in increase in emission characteristics of HSA and BSA and a significant blue spectra shift. In contrast, the interaction of NOR with HSA and BSA quenched the emission characteristics of HSA and BSA. The observed emission spectral shifts preclude the effective use of traditional univariate regression analysis of fluorescent data for the determination of EE and NOR concentrations in HSA and BSA samples. Multivariate partial-least-squares (PLS) regression analysis was utilized to correlate the changes in emission spectra with EE and NOR concentrations in HSA and BSA samples. The figures-of-merit of the developed PLS regression models were excellent, with limits of detection as low as 1.6×10(-8) M for EE and 2.4×10(-7) M for NOR and good linearity (R(2)>0.994985). The PLS models correctly predicted EE and NOR concentrations in independent validation HSA and BSA samples with a root-mean-square-percent-relative-error (RMS%RE) of less than 6.0% at physiological condition. On the contrary, the use of univariate regression resulted in poor predictions of EE and NOR in HSA and BSA samples, with RMS%RE larger than 40% at physiological conditions. High accuracy, low sensitivity, simplicity, low-cost with no prior analyte extraction or separation

  4. A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Paulino José García Nieto

    2016-05-01

    Full Text Available Remaining useful life (RUL estimation is considered as one of the most central points in the prognostics and health management (PHM. The present paper describes a nonlinear hybrid ABC–MARS-based model for the prediction of the remaining useful life of aircraft engines. Indeed, it is well-known that an accurate RUL estimation allows failure prevention in a more controllable way so that the effective maintenance can be carried out in appropriate time to correct impending faults. The proposed hybrid model combines multivariate adaptive regression splines (MARS, which have been successfully adopted for regression problems, with the artificial bee colony (ABC technique. This optimization technique involves parameter setting in the MARS training procedure, which significantly influences the regression accuracy. However, its use in reliability applications has not yet been widely explored. Bearing this in mind, remaining useful life values have been predicted here by using the hybrid ABC–MARS-based model from the remaining measured parameters (input variables for aircraft engines with success. A correlation coefficient equal to 0.92 was obtained when this hybrid ABC–MARS-based model was applied to experimental data. The agreement of this model with experimental data confirmed its good performance. The main advantage of this predictive model is that it does not require information about the previous operation states of the aircraft engine.

  5. Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique

    Science.gov (United States)

    Rounaghi, Mohammad Mahdi; Abbaszadeh, Mohammad Reza; Arashi, Mohammad

    2015-11-01

    One of the most important topics of interest to investors is stock price changes. Investors whose goals are long term are sensitive to stock price and its changes and react to them. In this regard, we used multivariate adaptive regression splines (MARS) model and semi-parametric splines technique for predicting stock price in this study. The MARS model as a nonparametric method is an adaptive method for regression and it fits for problems with high dimensions and several variables. semi-parametric splines technique was used in this study. Smoothing splines is a nonparametric regression method. In this study, we used 40 variables (30 accounting variables and 10 economic variables) for predicting stock price using the MARS model and using semi-parametric splines technique. After investigating the models, we select 4 accounting variables (book value per share, predicted earnings per share, P/E ratio and risk) as influencing variables on predicting stock price using the MARS model. After fitting the semi-parametric splines technique, only 4 accounting variables (dividends, net EPS, EPS Forecast and P/E Ratio) were selected as variables effective in forecasting stock prices.

  6. Multivariate analysis of nystatin and metronidazole in a semi-solid matrix by means of diffuse reflectance NIR spectroscopy and PLS regression.

    Science.gov (United States)

    Baratieri, Sabrina C; Barbosa, Juliana M; Freitas, Matheus P; Martins, José A

    2006-01-23

    A multivariate method of analysis of nystatin and metronidazole in a semi-solid matrix, based on diffuse reflectance NIR measurements and partial least squares regression, is reported. The product, a vaginal cream used in the antifungal and antibacterial treatment, is usually, quantitatively analyzed through microbiological tests (nystatin) and HPLC technique (metronidazole), according to pharmacopeial procedures. However, near infrared spectroscopy has demonstrated to be a valuable tool for content determination, given the rapidity and scope of the method. In the present study, it was successfully applied in the prediction of nystatin (even in low concentrations, ca. 0.3-0.4%, w/w, which is around 100,000 IU/5g) and metronidazole contents, as demonstrated by some figures of merit, namely linearity, precision (mean and repeatability) and accuracy.

  7. Using Apparent Density of Paper from Hardwood Kraft Pulps to Predict Sheet Properties, based on Unsupervised Classification and Multivariable Regression Techniques

    Directory of Open Access Journals (Sweden)

    Ofélia Anjos

    2015-07-01

    Full Text Available Paper properties determine the product application potential and depend on the raw material, pulping conditions, and pulp refining. The aim of this study was to construct mathematical models that predict quantitative relations between the paper density and various mechanical and optical properties of the paper. A dataset of properties of paper handsheets produced with pulps of Acacia dealbata, Acacia melanoxylon, and Eucalyptus globulus beaten at 500, 2500, and 4500 revolutions was used. Unsupervised classification techniques were combined to assess the need to perform separated prediction models for each species, and multivariable regression techniques were used to establish such prediction models. It was possible to develop models with a high goodness of fit using paper density as the independent variable (or predictor for all variables except tear index and zero-span tensile strength, both dry and wet.

  8. A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

    Science.gov (United States)

    Rossi, M.; Apuani, T.; Felletti, F.

    2009-04-01

    The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

  9. Multivariable Regression Analysis in Schistosoma mansoni-Infected Individuals in the Sudan Reveals Unique Immunoepidemiological Profiles in Uninfected, egg+ and Non-egg+ Infected Individuals.

    Science.gov (United States)

    Elfaki, Tayseer Elamin Mohamed; Arndts, Kathrin; Wiszniewsky, Anna; Ritter, Manuel; Goreish, Ibtisam A; Atti El Mekki, Misk El Yemen A; Arriens, Sandra; Pfarr, Kenneth; Fimmers, Rolf; Doenhoff, Mike; Hoerauf, Achim; Layland, Laura E

    2016-05-01

    In the Sudan, Schistosoma mansoni infections are a major cause of morbidity in school-aged children and infection rates are associated with available clean water sources. During infection, immune responses pass through a Th1 followed by Th2 and Treg phases and patterns can relate to different stages of infection or immunity. This retrospective study evaluated immunoepidemiological aspects in 234 individuals (range 4-85 years old) from Kassala and Khartoum states in 2011. Systemic immune profiles (cytokines and immunoglobulins) and epidemiological parameters were surveyed in n = 110 persons presenting patent S. mansoni infections (egg+), n = 63 individuals positive for S. mansoni via PCR in sera but egg negative (SmPCR+) and n = 61 people who were infection-free (Sm uninf). Immunoepidemiological findings were further investigated using two binary multivariable regression analysis. Nearly all egg+ individuals had no access to latrines and over 90% obtained water via the canal stemming from the Atbara River. With regards to age, infection and an egg+ status was linked to young and adolescent groups. In terms of immunology, S. mansoni infection per se was strongly associated with increased SEA-specific IgG4 but not IgE levels. IL-6, IL-13 and IL-10 were significantly elevated in patently-infected individuals and positively correlated with egg load. In contrast, IL-2 and IL-1β were significantly lower in SmPCR+ individuals when compared to Sm uninf and egg+ groups which was further confirmed during multivariate regression analysis. Schistosomiasis remains an important public health problem in the Sudan with a high number of patent individuals. In addition, SmPCR diagnostics revealed another cohort of infected individuals with a unique immunological profile and provides an avenue for future studies on non-patent infection states. Future studies should investigate the downstream signalling pathways/mechanisms of IL-2 and IL-1β as potential diagnostic markers in order to

  10. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha

    2014-12-08

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  11. Sparse reduced-rank regression with covariance estimation

    KAUST Repository

    Chen, Lisha; Huang, Jianhua Z.

    2014-01-01

    Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

  12. Using Multivariate Regression Model with Least Absolute Shrinkage and Selection Operator (LASSO) to Predict the Incidence of Xerostomia after Intensity-Modulated Radiotherapy for Head and Neck Cancer

    Science.gov (United States)

    Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Wu, Jia-Ming; Wang, Hung-Yu; Horng, Mong-Fong; Chang, Chun-Ming; Lan, Jen-Hong; Huang, Ya-Yu; Fang, Fu-Min; Leung, Stephen Wan

    2014-01-01

    Purpose The aim of this study was to develop a multivariate logistic regression model with least absolute shrinkage and selection operator (LASSO) to make valid predictions about the incidence of moderate-to-severe patient-rated xerostomia among head and neck cancer (HNC) patients treated with IMRT. Methods and Materials Quality of life questionnaire datasets from 206 patients with HNC were analyzed. The European Organization for Research and Treatment of Cancer QLQ-H&N35 and QLQ-C30 questionnaires were used as the endpoint evaluation. The primary endpoint (grade 3+ xerostomia) was defined as moderate-to-severe xerostomia at 3 (XER3m) and 12 months (XER12m) after the completion of IMRT. Normal tissue complication probability (NTCP) models were developed. The optimal and suboptimal numbers of prognostic factors for a multivariate logistic regression model were determined using the LASSO with bootstrapping technique. Statistical analysis was performed using the scaled Brier score, Nagelkerke R2, chi-squared test, Omnibus, Hosmer-Lemeshow test, and the AUC. Results Eight prognostic factors were selected by LASSO for the 3-month time point: Dmean-c, Dmean-i, age, financial status, T stage, AJCC stage, smoking, and education. Nine prognostic factors were selected for the 12-month time point: Dmean-i, education, Dmean-c, smoking, T stage, baseline xerostomia, alcohol abuse, family history, and node classification. In the selection of the suboptimal number of prognostic factors by LASSO, three suboptimal prognostic factors were fine-tuned by Hosmer-Lemeshow test and AUC, i.e., Dmean-c, Dmean-i, and age for the 3-month time point. Five suboptimal prognostic factors were also selected for the 12-month time point, i.e., Dmean-i, education, Dmean-c, smoking, and T stage. The overall performance for both time points of the NTCP model in terms of scaled Brier score, Omnibus, and Nagelkerke R2 was satisfactory and corresponded well with the expected values. Conclusions

  13. Aspects of nuclear penal liability

    International Nuclear Information System (INIS)

    Faria, N.M. de; Cruz, A.S.C. da

    1986-01-01

    Topics are treated with reference to articles of the Law 6.453 of october 17, 1977, relating to the nuclear penal liability. At the same time, the Penal Code disposes on illicits which may involve nuclear activity. With regard to the Jurisdiction, mention is made to the Federal Justice competence, due to the constitutional disposal. On the international field, the Convention on Physic Protection on Nuclear Material Transport disposes on illicit fact in which nuclear material may be involved. (Author) [pt

  14. Multivariable Regression Analysis in Schistosoma mansoni-Infected Individuals in the Sudan Reveals Unique Immunoepidemiological Profiles in Uninfected, egg+ and Non-egg+ Infected Individuals.

    Directory of Open Access Journals (Sweden)

    Tayseer Elamin Mohamed Elfaki

    2016-05-01

    Full Text Available In the Sudan, Schistosoma mansoni infections are a major cause of morbidity in school-aged children and infection rates are associated with available clean water sources. During infection, immune responses pass through a Th1 followed by Th2 and Treg phases and patterns can relate to different stages of infection or immunity.This retrospective study evaluated immunoepidemiological aspects in 234 individuals (range 4-85 years old from Kassala and Khartoum states in 2011. Systemic immune profiles (cytokines and immunoglobulins and epidemiological parameters were surveyed in n = 110 persons presenting patent S. mansoni infections (egg+, n = 63 individuals positive for S. mansoni via PCR in sera but egg negative (SmPCR+ and n = 61 people who were infection-free (Sm uninf. Immunoepidemiological findings were further investigated using two binary multivariable regression analysis.Nearly all egg+ individuals had no access to latrines and over 90% obtained water via the canal stemming from the Atbara River. With regards to age, infection and an egg+ status was linked to young and adolescent groups. In terms of immunology, S. mansoni infection per se was strongly associated with increased SEA-specific IgG4 but not IgE levels. IL-6, IL-13 and IL-10 were significantly elevated in patently-infected individuals and positively correlated with egg load. In contrast, IL-2 and IL-1β were significantly lower in SmPCR+ individuals when compared to Sm uninf and egg+ groups which was further confirmed during multivariate regression analysis.Schistosomiasis remains an important public health problem in the Sudan with a high number of patent individuals. In addition, SmPCR diagnostics revealed another cohort of infected individuals with a unique immunological profile and provides an avenue for future studies on non-patent infection states. Future studies should investigate the downstream signalling pathways/mechanisms of IL-2 and IL-1β as potential diagnostic markers

  15. The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment — Beyond classical regression

    Directory of Open Access Journals (Sweden)

    Stefan J. Teipel

    2015-01-01

    Penalized regression yielded more parsimonious models than unpenalized stepwise regression for the integration of multiregional and multimodal imaging information. The advantage of penalized regression was particularly strong with a high number of collinear predictors.

  16. Study of cyanotoxins presence from experimental cyanobacteria concentrations using a new data mining methodology based on multivariate adaptive regression splines in Trasona reservoir (Northern Spain).

    Science.gov (United States)

    Garcia Nieto, P J; Sánchez Lasheras, F; de Cos Juez, F J; Alonso Fernández, J R

    2011-11-15

    There is an increasing need to describe cyanobacteria blooms since some cyanobacteria produce toxins, termed cyanotoxins. These latter can be toxic and dangerous to humans as well as other animals and life in general. It must be remarked that the cyanobacteria are reproduced explosively under certain conditions. This results in algae blooms, which can become harmful to other species if the cyanobacteria involved produce cyanotoxins. In this research work, the evolution of cyanotoxins in Trasona reservoir (Principality of Asturias, Northern Spain) was studied with success using the data mining methodology based on multivariate adaptive regression splines (MARS) technique. The results of the present study are two-fold. On one hand, the importance of the different kind of cyanobacteria over the presence of cyanotoxins in the reservoir is presented through the MARS model and on the other hand a predictive model able to forecast the possible presence of cyanotoxins in a short term was obtained. The agreement of the MARS model with experimental data confirmed the good performance of the same one. Finally, conclusions of this innovative research are exposed. Copyright © 2011 Elsevier B.V. All rights reserved.

  17. The effect of hospital mergers on long-term sickness absence among hospital employees: a fixed effects multivariate regression analysis using panel data.

    Science.gov (United States)

    Kjekshus, Lars Erik; Bernstrøm, Vilde Hoff; Dahl, Espen; Lorentzen, Thomas

    2014-02-03

    Hospitals are merging to become more cost-effective. Mergers are often complex and difficult processes with variable outcomes. The aim of this study was to analyze the effect of mergers on long-term sickness absence among hospital employees. Long-term sickness absence was analyzed among hospital employees (N = 107 209) in 57 hospitals involved in 23 mergers in Norway between 2000 and 2009. Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis using panel data with years-since-merger as the independent variable. We found a significant but modest effect of mergers on long-term sickness absence in the year of the merger, and in years 2, 3 and 4; analyzed by gender there was a significant effect for women, also for these years, but only in year 4 for men. However, men are less represented among the hospital workforce; this could explain the lack of significance. Mergers has a significant effect on employee health that should be taken into consideration when deciding to merge hospitals. This study illustrates the importance of analyzing the effects of mergers over several years and the need for more detailed analyses of merger processes and of the changes that may occur as a result of such mergers.

  18. A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

    Directory of Open Access Journals (Sweden)

    Goyal Neeraj

    2010-01-01

    Full Text Available To compare the accuracy of artificial neural network (ANN analysis and multi-variate regression analysis (MVRA for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL. A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC (r2 . For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL.

  19. Application of least square support vector machine and multivariate adaptive regression spline models in long term prediction of river water pollution

    Science.gov (United States)

    Kisi, Ozgur; Parmar, Kulwinder Singh

    2016-03-01

    This study investigates the accuracy of least square support vector machine (LSSVM), multivariate adaptive regression splines (MARS) and M5 model tree (M5Tree) in modeling river water pollution. Various combinations of water quality parameters, Free Ammonia (AMM), Total Kjeldahl Nitrogen (TKN), Water Temperature (WT), Total Coliform (TC), Fecal Coliform (FC) and Potential of Hydrogen (pH) monitored at Nizamuddin, Delhi Yamuna River in India were used as inputs to the applied models. Results indicated that the LSSVM and MARS models had almost same accuracy and they performed better than the M5Tree model in modeling monthly chemical oxygen demand (COD). The average root mean square error (RMSE) of the LSSVM and M5Tree models was decreased by 1.47% and 19.1% using MARS model, respectively. Adding TC input to the models did not increase their accuracy in modeling COD while adding FC and pH inputs to the models generally decreased the accuracy. The overall results indicated that the MARS and LSSVM models could be successfully used in estimating monthly river water pollution level by using AMM, TKN and WT parameters as inputs.

  20. A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

    International Nuclear Information System (INIS)

    Neeraj K Goyal, Abhay Kumar; Sameer Trivedi

    2010-01-01

    To compare the accuracy of artificial neural network (ANN) analysis and multivariate regression analysis (MVRA) for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL). A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values) were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values) from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC) (r2 ). For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL (Author).

  1. Comparative Analysis for Robust Penalized Spline Smoothing Methods

    Directory of Open Access Journals (Sweden)

    Bin Wang

    2014-01-01

    Full Text Available Smoothing noisy data is commonly encountered in engineering domain, and currently robust penalized regression spline models are perceived to be the most promising methods for coping with this issue, due to their flexibilities in capturing the nonlinear trends in the data and effectively alleviating the disturbance from the outliers. Against such a background, this paper conducts a thoroughly comparative analysis of two popular robust smoothing techniques, the M-type estimator and S-estimation for penalized regression splines, both of which are reelaborated starting from their origins, with their derivation process reformulated and the corresponding algorithms reorganized under a unified framework. Performances of these two estimators are thoroughly evaluated from the aspects of fitting accuracy, robustness, and execution time upon the MATLAB platform. Elaborately comparative experiments demonstrate that robust penalized spline smoothing methods possess the capability of resistance to the noise effect compared with the nonrobust penalized LS spline regression method. Furthermore, the M-estimator exerts stable performance only for the observations with moderate perturbation error, whereas the S-estimator behaves fairly well even for heavily contaminated observations, but consuming more execution time. These findings can be served as guidance to the selection of appropriate approach for smoothing the noisy data.

  2. Prosthetic alignment after total knee replacement is not associated with dissatisfaction or change in Oxford Knee Score: A multivariable regression analysis.

    Science.gov (United States)

    Huijbregts, Henricus J T A M; Khan, Riaz J K; Fick, Daniel P; Jarrett, Olivia M; Haebich, Samantha

    2016-06-01

    Approximately 18% of the patients are dissatisfied with the result of total knee replacement. However, the relation between dissatisfaction and prosthetic alignment has not been investigated before. We retrospectively analysed prospectively gathered data of all patients who had a primary TKR, preoperative and one-year postoperative Oxford Knee Scores (OKS) and postoperative computed tomography (CT). The CT protocol measures hip-knee-ankle (HKA) angle, and coronal, sagittal and axial component alignment. Satisfaction was defined using a five-item Likert scale. We dichotomised dissatisfaction by combining '(very) dissatisfied' and 'neutral/not sure'. Associations with dissatisfaction and change in OKS were calculated using multivariable logistic and linear regression models. 230 TKRs were implanted in 105 men and 106 women. At one year, 12% were (very) dissatisfied and 10% neutral. Coronal alignment of the femoral component was 0.5 degrees more accurate in patients who were satisfied at one year. The other alignment measurements were not different between satisfied and dissatisfied patients. All radiographic measurements had a P-value>0.10 on univariate analyses. At one year, dissatisfaction was associated with the three-months OKS. Change in OKS was associated with three-months OKS, preoperative physical SF-12, preoperative pain and cruciate retaining design. Neither mechanical axis, nor component alignment, is associated with dissatisfaction at one year following TKR. Patients get the best outcome when pain reduction and function improvement are optimal during the first three months and when the indication to embark on surgery is based on physical limitations rather than on a high pain score. 2. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Seasonal variation of benzo(a)pyrene in the Spanish airborne PM10. Multivariate linear regression model applied to estimate BaP concentrations.

    Science.gov (United States)

    Callén, M S; López, J M; Mastral, A M

    2010-08-15

    The estimation of benzo(a)pyrene (BaP) concentrations in ambient air is very important from an environmental point of view especially with the introduction of the Directive 2004/107/EC and due to the carcinogenic character of this pollutant. A sampling campaign of particulate matter less or equal than 10 microns (PM10) carried out during 2008-2009 in four locations of Spain was collected to determine experimentally BaP concentrations by gas chromatography mass-spectrometry mass-spectrometry (GC-MS-MS). Multivariate linear regression models (MLRM) were used to predict BaP air concentrations in two sampling places, taking PM10 and meteorological variables as possible predictors. The model obtained with data from two sampling sites (all sites model) (R(2)=0.817, PRESS/SSY=0.183) included the significant variables like PM10, temperature, solar radiation and wind speed and was internally and externally validated. The first validation was performed by cross validation and the last one by BaP concentrations from previous campaigns carried out in Zaragoza from 2001-2004. The proposed model constitutes a first approximation to estimate BaP concentrations in urban atmospheres with very good internal prediction (Q(CV)(2)=0.813, PRESS/SSY=0.187) and with the maximal external prediction for the 2001-2002 campaign (Q(ext)(2)=0.679 and PRESS/SSY=0.321) versus the 2001-2004 campaign (Q(ext)(2)=0.551, PRESS/SSY=0.449). Copyright 2010 Elsevier B.V. All rights reserved.

  4. Seasonal variation of benzo(a)pyrene in the Spanish airborne PM10. Multivariate linear regression model applied to estimate BaP concentrations

    International Nuclear Information System (INIS)

    Callen, M.S.; Lopez, J.M.; Mastral, A.M.

    2010-01-01

    The estimation of benzo(a)pyrene (BaP) concentrations in ambient air is very important from an environmental point of view especially with the introduction of the Directive 2004/107/EC and due to the carcinogenic character of this pollutant. A sampling campaign of particulate matter less or equal than 10 microns (PM10) carried out during 2008-2009 in four locations of Spain was collected to determine experimentally BaP concentrations by gas chromatography mass-spectrometry mass-spectrometry (GC-MS-MS). Multivariate linear regression models (MLRM) were used to predict BaP air concentrations in two sampling places, taking PM10 and meteorological variables as possible predictors. The model obtained with data from two sampling sites (all sites model) (R 2 = 0.817, PRESS/SSY = 0.183) included the significant variables like PM10, temperature, solar radiation and wind speed and was internally and externally validated. The first validation was performed by cross validation and the last one by BaP concentrations from previous campaigns carried out in Zaragoza from 2001-2004. The proposed model constitutes a first approximation to estimate BaP concentrations in urban atmospheres with very good internal prediction (Q CV 2 =0.813, PRESS/SSY = 0.187) and with the maximal external prediction for the 2001-2002 campaign (Q ext 2 =0.679 and PRESS/SSY = 0.321) versus the 2001-2004 campaign (Q ext 2 =0.551, PRESS/SSY = 0.449).

  5. Personal, social, and game-related correlates of active and non-active gaming among dutch gaming adolescents: survey-based multivariable, multilevel logistic regression analyses.

    Science.gov (United States)

    Simons, Monique; de Vet, Emely; Chinapaw, Mai Jm; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-04-04

    Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games-active games-seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a correlate of both active and non-active gaming

  6. Personal, Social, and Game-Related Correlates of Active and Non-Active Gaming Among Dutch Gaming Adolescents: Survey-Based Multivariable, Multilevel Logistic Regression Analyses

    Science.gov (United States)

    de Vet, Emely; Chinapaw, Mai JM; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-01-01

    Background Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games—active games—seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. Objective The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. Methods A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Results Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a

  7. El consentimiento en materia penal

    Directory of Open Access Journals (Sweden)

    Camilo Iván Machado Rodríguez

    2012-12-01

    Full Text Available Se plantea un estudio de las diferentes posturas dogmáticas que se han suscitado en la doctrina jurídico-penal en torno a la relevancia del instituto del consentimiento, como su regulación, recorriendo las legislaciones penales española, alemana, italiana y colombiana. Así mismo, se toman en consideración las recientes posturas, en donde se entiende el consentimiento como un supuesto de autopuesta en peligro, o como uno de heteropuesta en peligro de la víctima. Se propone un entendimiento de la figura desde la óptica de la teoría de la imputación objetiva, y para ello se incluye el consentimiento como causa de ausencia de la imputación objetiva.

  8. La legitimidad del derecho penal

    Directory of Open Access Journals (Sweden)

    Francisco Bernate-Ochoa

    2010-03-01

    Full Text Available El interrogante sobre la legitimidad del derecho penal se ha convertido en un asunto medular dentro de los estudios contemporáneos sobre la materia, dado que hoy en día se reconoce que a partir de la solución a este interrogante teórico se puede asumir la tarea de construir un sistema. El panorama contemporáneo nos ofrece dos soluciones al respecto: por una parte, se sostiene que la legitimación del derecho penal emana de la Constitución, y se prescinde de una construcción sistémica del delito en aras de la obtención de consecuencias acordes con lo planteado en la Carta Política. Por otra, desde una propuesta -de corte normativista- se entiende que la legitimación del derecho penal debe encontrarse en la sociedad, y a partir del entendimiento de ésta se encuentra la necesidad de aquél, lo cual ejerce una influencia en la construcción del sistema del delito.

  9. STRONG ORACLE OPTIMALITY OF FOLDED CONCAVE PENALIZED ESTIMATION.

    Science.gov (United States)

    Fan, Jianqing; Xue, Lingzhou; Zou, Hui

    2014-06-01

    Folded concave penalization methods have been shown to enjoy the strong oracle property for high-dimensional sparse estimation. However, a folded concave penalization problem usually has multiple local solutions and the oracle property is established only for one of the unknown local solutions. A challenging fundamental issue still remains that it is not clear whether the local optimum computed by a given optimization algorithm possesses those nice theoretical properties. To close this important theoretical gap in over a decade, we provide a unified theory to show explicitly how to obtain the oracle solution via the local linear approximation algorithm. For a folded concave penalized estimation problem, we show that as long as the problem is localizable and the oracle estimator is well behaved, we can obtain the oracle estimator by using the one-step local linear approximation. In addition, once the oracle estimator is obtained, the local linear approximation algorithm converges, namely it produces the same estimator in the next iteration. The general theory is demonstrated by using four classical sparse estimation problems, i.e., sparse linear regression, sparse logistic regression, sparse precision matrix estimation and sparse quantile regression.

  10. Refractory reverse amblyopia with atropine penalization

    Directory of Open Access Journals (Sweden)

    Preeti Ajit Patil

    2010-01-01

    Full Text Available Pharmacological penalization with atropine has been shown to be equally effective as conventional occlusion therapy in the treatment of amblyopia in children. Reverse amblyopia of the sound eye with atropine penalization has been reported before, but is more common in cases where the effect is augmented with optical penalization and is mostly reversible. We report a case of reverse amblyopia with atropine penalization, in a 4-year-old girl, which was refractory to treatment. This report highlights the need for strict monitoring of the vision in the sound eye and regular follow-up in children undergoing amblyopia treatment.

  11. Seguridad ciudadana y respuesta penal

    Directory of Open Access Journals (Sweden)

    Beatriz Scapusio Minvielle

    2015-10-01

    Full Text Available El concepto de seguridad ciudadana será empleado en esta comunicación en su sentido restringido, vinculado al sentimiento de confianza de la población de no verse expuesta a hechos de violencia física, tengan origen éstos en actos individuales o sociales.  (...Contenido: Diferentes expresiones de la seguridad ciudadana. La respuesta penal. Evaluación global del problema. El desafío dogmático. Conclusiones

  12. Iterative Brinkman penalization for remeshed vortex methods

    DEFF Research Database (Denmark)

    Hejlesen, Mads Mølholm; Koumoutsakos, Petros; Leonard, Anthony

    2015-01-01

    We introduce an iterative Brinkman penalization method for the enforcement of the no-slip boundary condition in remeshed vortex methods. In the proposed method, the Brinkman penalization is applied iteratively only in the neighborhood of the body. This allows for using significantly larger time...

  13. Proyecto de reforma del Proceso Penal

    Directory of Open Access Journals (Sweden)

    Beatriz Scapusio

    2014-04-01

    Full Text Available El Anteproyecto de Código de Proceso PenalExpositora: Beatriz ScapusioLa Imputabilidad Aportes dogmáticos para un tema clave de la responsablidad penalExpositor: Dardo Preza RestucciaEstructuras procesales en el proceso de conocimiento y en el proceso de ejecuciónExpositora: Raquel Landeira

  14. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

    Science.gov (United States)

    Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

    2018-03-01

    Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

  15. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

    Directory of Open Access Journals (Sweden)

    Ying Peng

    2018-03-01

    Full Text Available Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

  16. Significance of volatile compounds produced by spoilage bacteria in vacuum-packed cold-smoked salmon ( Salmo salar ) analyzed by GC-MS and multivariate regression

    DEFF Research Database (Denmark)

    Jørgensen, Lasse Vigel; Huss, Hans Henrik; Dalgaard, Paw

    2001-01-01

    alcohols, which were produced by microbial activity. Partial least- squares regression of volatile compounds and sensory results allowed for a multiple compound quality index to be developed. This index was based on volatile bacterial metabolites, 1- propanol and 2-butanone, and 2-furan......, 1- penten-3-ol, and 1-propanol. The potency and importance of these compounds was confirmed by gas chromatography- olfactometry. The present study provides valuable information on the bacterial reactions responsible for spoilage off-flavors of cold-smoked salmon, which can be used to develop...

  17. [Penal institutions in Porto Azzuro].

    Science.gov (United States)

    Ciccotti, R

    1976-01-01

    Prior to describing the environmental and human situation of the Porto Azzurro penal Institutions, the Author devotes a chapter to the historical part and gives an outline of the most important events that, in 1600 or thereabouts, led to the construction of the Fort S. Giacoma (where the penitentiary is presently sited), which, after a number of vicissitudes and transfers of title, was finally destined for use, in 1900, as a prison establishment. The subsequent and, in particular, the recent building re-structurations, have radically changed the penitentiary in order to make it more in line with the functions required by the present prison policy. After describing the establishment's setup, which includes many institutes, the Author passes on to consider the problems of personnel and, in particular, of the military staff. In the central chapter on intramural life, he makes an in-depth review of the methods and means of treatment, some of which are proper of this particular environment. In illustrating such convicts' activities, as working, leisure time, education, relationship with the extramural world, the Author lays stress on the always present objective: that directed at helping convicts re-enter social life. In conjunction with health services and religious services, the Author deals at length with the delicate moment of the "audience", viewed as a therapeutic means indispensiable for establishing a valid re-educational contribution. The discipline and discharges conclude the description of the Porto Azzurro penal Institutions, whose environment and various treatment methods in use before the implementation of the new penitentiary System, are dealt with in detail by the Author.

  18. Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

    Science.gov (United States)

    Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

    2017-03-05

    The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

  19. Oil condition monitoring of gears onboard ships using a regression approach for multivariate T2 control charts

    DEFF Research Database (Denmark)

    Henneberg, Morten; Jørgensen, Bent; Eriksen, René Lynge

    2016-01-01

    In this paper, we present an oil condition and wear debris evaluation method for ship thruster gears using T2 statistics to form control charts from a multi-sensor platform. The proposed method takes into account the different ambient conditions by multiple linear regression on the mean value...... only quasi-stationary data are included in phase I of the T2 statistics. Data from two thruster gears onboard two different ships are presented and analyzed, and the selection of the phase I data size is discussed. A graphic overview for quick localization of T2 signaling is also demonstrated using...... spider plots. Finally, progression and trending of the T2 statistics are investigated using orthogonal polynomials for a fix-sized data window....

  20. Utilização de regressão multivariada para avaliação espectrofotométrica da demanda química de oxigênio em amostras de relevância ambiental Use of multivariate regression in spectrophotometric evaluation of chemical oxigen demand in samples of environmental relevance

    Directory of Open Access Journals (Sweden)

    Patricio Peralta-Zamora

    2005-10-01

    Full Text Available In this work, a partial least squares regression routine was used to develop a multivariate calibration model to predict the chemical oxygen demand (COD in substrates of environmental relevance (paper effluents and landfill leachates from UV-Vis spectral data. The calibration models permit the fast determination of the COD with typical relative errors lower by 10% with respect to the conventional methodology.

  1. Race Making in a Penal Institution.

    Science.gov (United States)

    Walker, Michael L

    2016-01-01

    This article provides a ground-level investigation into the lives of penal inmates, linking the literature on race making and penal management to provide an understanding of racial formation processes in a modern penal institution. Drawing on 135 days of ethnographic data collected as an inmate in a Southern California county jail system, the author argues that inmates are subjected to two mutually constitutive racial projects--one institutional and the other microinteractional. Operating in symbiosis within a narrative of risk management, these racial projects increase (rather than decrease) incidents of intraracial violence and the potential for interracial violence. These findings have implications for understanding the process of racialization and evaluating the effectiveness of penal management strategies.

  2. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  3. Aortic and Hepatic Contrast Enhancement During Hepatic-Arterial and Portal Venous Phase Computed Tomography Scanning: Multivariate Linear Regression Analysis Using Age, Sex, Total Body Weight, Height, and Cardiac Output.

    Science.gov (United States)

    Masuda, Takanori; Nakaura, Takeshi; Funama, Yoshinori; Higaki, Toru; Kiguchi, Masao; Imada, Naoyuki; Sato, Tomoyasu; Awai, Kazuo

    We evaluated the effect of the age, sex, total body weight (TBW), height (HT) and cardiac output (CO) of patients on aortic and hepatic contrast enhancement during hepatic-arterial phase (HAP) and portal venous phase (PVP) computed tomography (CT) scanning. This prospective study received institutional review board approval; prior informed consent to participate was obtained from all 168 patients. All were examined using our routine protocol; the contrast material was 600 mg/kg iodine. Cardiac output was measured with a portable electrical velocimeter within 5 minutes of starting the CT scan. We calculated contrast enhancement (per gram of iodine: [INCREMENT]HU/gI) of the abdominal aorta during the HAP and of the liver parenchyma during the PVP. We performed univariate and multivariate linear regression analysis between all patient characteristics and the [INCREMENT]HU/gI of aortic- and liver parenchymal enhancement. Univariate linear regression analysis demonstrated statistically significant correlations between the [INCREMENT]HU/gI and the age, sex, TBW, HT, and CO (all P linear regression analysis showed that only the TBW and CO were of independent predictive value (P linear regression analysis only the TBW and CO were significantly correlated with aortic and liver parenchymal enhancement; the age, sex, and HT were not. The CO was the only independent factor affecting aortic and liver parenchymal enhancement at hepatic CT when the protocol was adjusted for the TBW.

  4. Multivariate analysis with LISREL

    CERN Document Server

    Jöreskog, Karl G; Y Wallentin, Fan

    2016-01-01

    This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

  5. Robust multivariate analysis

    CERN Document Server

    J Olive, David

    2017-01-01

    This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

  6. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  7. A Tutela Penal dos Direitos Humanos

    Directory of Open Access Journals (Sweden)

    Paulo Cesar Correa Borges

    2012-04-01

    Full Text Available A proteção penal dos direitos humanos tem dois aspectos decorrentes do garantismo penal: 1 limite para a persecução penal; 2 objetividade jurídica das normas incriminadoras. O conceito de direitos humanos para fins de tutela penal prescinde da sua classificação geracional, mas determina o reconhecimento de sua historicidade e, principalmente, a sua construção a partir das mobilizações e movimentos sociais. A vulnerabilidade dos grupos humanos que são difusa e sistematicamente discriminados ou violados deve ser o critério para a definição do objeto jurídico da norma incriminadora, para manter coerência e viabilizar a aplicação do princípio da complementariedade entre a repressão interna e a persecução internacional, compatibilizando o Direito Penal interno e o Internacional.

  8. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  9. EN BUSCA DE OTRO DERECHO PENAL

    Directory of Open Access Journals (Sweden)

    Geovana Andrea Vallejo Jiménez

    2011-05-01

    Full Text Available Este texto pretende describir algunos de los problemas contemporáneos del derecho penal en Colombia, así como las orientaciones que han asumido las líneas de investigación de los grupos de las universidades Eafit, de Antioquia y de Medellín en la búsqueda de soluciones a estos problemas, y la propuesta que se tiene a partir de la fundamentación de línea de investigación en Derecho Penal en la Institución Universitaria de Envigado.

  10. La Corte Penal Internacional: abriendo caminos

    Directory of Open Access Journals (Sweden)

    Alfredo Etcheberry

    2009-01-01

    Full Text Available A partir del análisis de las decisiones de la Corte Penal Internacional en el Caso Lubanga y la solicitud del Fiscal de detener al Presidente en ejercicio de Sudán, los autores analizan los desafíos y perspectivas del trabajo de la Corte Penal Internacional, particularmente en lo relativo a cómo se ha configurado su labor después de una etapa inicial dedicada a esclarecer su rol y constitución.

  11. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

    Science.gov (United States)

    Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-01

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

  12. Comparing near-infrared conventional diffuse reflectance spectroscopy and hyperspectral imaging for determination of the bulk properties of solid samples by multivariate regression: determination of Mooney viscosity and plasticity indices of natural rubber.

    Science.gov (United States)

    Juliano da Silva, Carlos; Pasquini, Celio

    2015-01-21

    Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample

  13. Reflection on penal policy in nuclear matters

    International Nuclear Information System (INIS)

    Cisse, A.

    1996-01-01

    This document expresses ethical reflexions as far as nuclear energy development is concerned. The potential diversion of the peaceful use of nuclear energy results in the necessity of a criminal policy which would control the nuclear regulations. For each potential nuclear infringement, systems of laws are established either to prevent damages or to penalize them. (TEC)

  14. Penal Policies In Bulgaria And Poland

    Directory of Open Access Journals (Sweden)

    Simona Mihaiu

    2016-12-01

    Full Text Available The contemporary european studies underline the necessity of adoption of an european model, in order to assure the compliance with the fundamental rights and liberties of people deprived of liberty. But the visions of the model favour one of the two opposite tendencies, which are invariable present in theoretical debates and penal politics

  15. Mapping the Conditions of Penal Hope

    Directory of Open Access Journals (Sweden)

    David Brown

    2013-11-01

    Full Text Available This article examines the conditions of penal optimism behind suggestions that the penal expansionism of the last three decades may be at a ‘turning point’. The article proceeds by outlining David Green’s suggested catalysts of penal reform and considers how applicable they are in the Australian context. Green’s suggested catalysts are: the cycles and saturation thesis; shifts in the dominant conception of the offender; the GFC and budgetary constraints; the drop in crime; the emergence of the prisoner re-entry movement; apparent shifts in public opinion; the influence of evangelical Christian ideas and the Right on Crime initiative. The article then considers a number of other possible catalysts or forces: the role of trade unions; the role of courts; the emergence of recidivism as a political issue; the influence of ’evidence based’/’what works’’ discourse; and the emergence of justice reinvestment (JR. The article concludes with some comments about the capacity of criminology and criminologists to contribute to penal reductionism, offering an optimistic assessment for the prospects of a reflexive criminology that engages in and engenders a wider politics around criminal justice issues.

  16. An Iterative Brinkman penalization for particle vortex methods

    DEFF Research Database (Denmark)

    Walther, Jens Honore; Hejlesen, Mads Mølholm; Leonard, A.

    2013-01-01

    We present an iterative Brinkman penalization method for the enforcement of the no-slip boundary condition in vortex particle methods. This is achieved by implementing a penalization of the velocity field using iteration of the penalized vorticity. We show that using the conventional Brinkman...... condition. These are: the impulsively started flow past a cylinder, the impulsively started flow normal to a flat plate, and the uniformly accelerated flow normal to a flat plate. The iterative penalization algorithm is shown to give significantly improved results compared to the conventional penalization...

  17. Evaluation of Penalized and Nonpenalized Methods for Disease Prediction with Large-Scale Genetic Data

    Directory of Open Access Journals (Sweden)

    Sungho Won

    2015-01-01

    Full Text Available Owing to recent improvement of genotyping technology, large-scale genetic data can be utilized to identify disease susceptibility loci and this successful finding has substantially improved our understanding of complex diseases. However, in spite of these successes, most of the genetic effects for many complex diseases were found to be very small, which have been a big hurdle to build disease prediction model. Recently, many statistical methods based on penalized regressions have been proposed to tackle the so-called “large P and small N” problem. Penalized regressions including least absolute selection and shrinkage operator (LASSO and ridge regression limit the space of parameters, and this constraint enables the estimation of effects for very large number of SNPs. Various extensions have been suggested, and, in this report, we compare their accuracy by applying them to several complex diseases. Our results show that penalized regressions are usually robust and provide better accuracy than the existing methods for at least diseases under consideration.

  18. CMS penalizes 758 hospitals for safety incidents

    Directory of Open Access Journals (Sweden)

    Robbins RA

    2015-12-01

    Full Text Available No abstract available. Article truncated after 150 words. The Centers for Medicare and Medicaid Services (CMS is penalizing 758 hospitals with higher rates of patient safety incidents, and more than half of those were also fined last year, as reported by Kaiser Health News (1. Among the hospitals being financially punished are some well-known institutions, including Yale New Haven Hospital, Medstar Washington Hospital Center in DC, Grady Memorial Hospital, Northwestern Memorial Hospital in Chicago, Indiana University Health, Brigham and Womens Hospital, Tufts Medical Center, University of North Carolina Hospital, the Cleveland Clinic, Hospital of the University of Pennsylvania, Parkland Health and Hospital, and the University of Virginia Medical Center (Complete List of Hospitals Penalized 2016. In the Southwest the list includes Banner University Medical Center in Tucson, Ronald Reagan UCLA Medical Center, Stanford Health Care, Denver Health Medical Center and the University of New Mexico Medical Center (for list of Southwest hospitals see Appendix 1. In total, CMS ...

  19. Kebijakan Penal Mengenai Kriminalisasi Di Bidang Keuangan

    OpenAIRE

    Luthan, Salman

    2009-01-01

    Research of penal policy on criminalization in financial affairs discusses two main problems: regulating policy on criminal offences, and regulating policy on criminal sanction for financial offences. The regulating policy on criminal offences shows an increase of various conducts that have been criminalized by legislator as a consequence of social change, economic and trade globalization, as well as technological development. Justification of criminalization base on liberal individualiatic t...

  20. Penalized feature selection and classification in bioinformatics

    OpenAIRE

    Ma, Shuangge; Huang, Jian

    2008-01-01

    In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classific...

  1. Environmental protection - Penal Law. 2nd ed.

    International Nuclear Information System (INIS)

    Sack, H.J.

    1980-01-01

    The 18th Amendment of the Penal Law - Law on the Abatement of Environmental Delinquency - (18. StrAendG) has now been passed. It has been promulgated on March 28, 1980 and has come into force on July 1, 1980. Through this amendment, a large number of the provisions of the environmental law regarding sanctions has been incorporated into the Penal Code. Persons concerned with environmental protection and pollution control will also in future need such a textbook with comments as a guide to the most important provisions on sanctions and fixed penalties. The 18th Amendment of the Penal Code does not cover all the provisions on sanctions to be applied in the field of environmental protection, a number of regulations still remains part of other, special laws. The same applies to the provisions on penalties which are laid down in a variety of individual laws and regulations, as a comprehensive code of environmental laws still remains to be established. This first part of the textbook in loose-leaf form deals mainly with the new provisions of sections 311d, 311e, 324, and 325. The other facts of the 18th Amendment will be discussed in the second part. As the regulations have, for the most part, not been completly revised or newly inserted, parts 1/3 of the first edition of this textbook can still be used as a help in analysing the existing provisions. (orig./HP) [de

  2. Environmental protection - Penal Law. Umweltschutz-Strafrecht

    Energy Technology Data Exchange (ETDEWEB)

    Sack, H J

    1980-01-01

    The 18th Amendment of the Penal Law - Law on the Abatement of Environmental Delinquency - (18. StrAendG) has now been passed. It has been promulgated on March 28, 1980 and has come into force on July 1, 1980. Through this amendment, a large number of the provisions of the environmental law regarding sanctions has been incorporated into the Penal Code. Persons concerned with environmental protection and pollution control will also in future need such a textbook with comments as a guide to the most important provisions on sanctions and fixed penalties. The 18th Amendment of the Penal Code does not cover all the provisions on sanctions to be applied in the field of environmental protection, a number of regulations still remains part of other, special laws. The same applies to the provisions on penalties which are laid down in a variety of individual laws and regulations, as a comprehensive code of environmental laws still remains to be established. This first part of the textbook in loose-leaf form deals mainly with the new provisions of sections 311d, 311e, 324, and 325. The other facts of the 18th Amendment will be discussed in the second part. As the regulations have, for the most part, not been completly revised or newly inserted, parts 1/3 of the first edition of this textbook can still be used as a help in analysing the existing provisions.

  3. Performance of penalized maximum likelihood in estimation of genetic covariances matrices

    Directory of Open Access Journals (Sweden)

    Meyer Karin

    2011-11-01

    Full Text Available Abstract Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of regularized estimation of covariance components in a maximum likelihood framework, imposing a penalty on the likelihood designed to reduce sampling variation. In particular, penalties that "borrow strength" from the phenotypic covariance matrix are considered. Methods An extensive simulation study was carried out to investigate the reduction in average 'loss', i.e. the deviation in estimated matrices from the population values, and the accompanying bias for a range of parameter values and sample sizes. A number of penalties are examined, penalizing either the canonical eigenvalues or the genetic covariance or correlation matrices. In addition, several strategies to determine the amount of penalization to be applied, i.e. to estimate the appropriate tuning factor, are explored. Results It is shown that substantial reductions in loss for estimates of genetic covariance can be achieved for small to moderate sample sizes. While no penalty performed best overall, penalizing the variance among the estimated canonical eigenvalues on the logarithmic scale or shrinking the genetic towards the phenotypic correlation matrix appeared most advantageous. Estimating the tuning factor using cross-validation resulted in a loss reduction 10 to 15% less than that obtained if population values were known. Applying a mild penalty, chosen so that the deviation in likelihood from the maximum was non-significant, performed as well if not better than cross-validation and can be recommended as a pragmatic strategy. Conclusions Penalized maximum likelihood estimation provides the means to 'make the most' of limited and precious data and facilitates more stable estimation for multi-dimensional analyses. It should

  4. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  5. SANCTIONING DUPLICATION IN ADMINISTRATIVE AND PENAL AREAS

    Directory of Open Access Journals (Sweden)

    José Manuel Cabrera Delgado

    2014-12-01

    Full Text Available This article provides a first approach from the point of view of jurisprudence, to the recurring problem of concurrency sanctions in cases where further intervention of the courts has become necessary for administrative action. In this regard, the main judgments of both the Constitutional Court and the Supreme Court is, that have shaped the decisions that must be applied from the administrative level, in particular by educational inspectors, when it is foreseeable that it can produce a duplication of disciplinary procedures in the two areas, penal and administrative.

  6. L1-Penalized N-way PLS for subset of electrodes selection in BCI experiments

    Science.gov (United States)

    Eliseyev, Andrey; Moro, Cecile; Faber, Jean; Wyss, Alexander; Torres, Napoleon; Mestais, Corinne; Benabid, Alim Louis; Aksenova, Tetiana

    2012-08-01

    Recently, the N-way partial least squares (NPLS) approach was reported as an effective tool for neuronal signal decoding and brain-computer interface (BCI) system calibration. This method simultaneously analyzes data in several domains. It combines the projection of a data tensor to a low dimensional space with linear regression. In this paper the L1-Penalized NPLS is proposed for sparse BCI system calibration, allowing uniting the projection technique with an effective selection of subset of features. The L1-Penalized NPLS was applied for the binary self-paced BCI system calibration, providing selection of electrodes subset. Our BCI system is designed for animal research, in particular for research in non-human primates.

  7. To What Extent are Domestic Penal Laws Retroactive for Crime ...

    African Journals Online (AJOL)

    Nafiisah

    Hard or soft law most countries have at least a piece of statutory enactment, which provides for the non-retroactivity of penal law. Non retroactivity of penal laws also forms part of fundamental rights of the citizens in the Constitution, the supreme law of the country of the Republic of Mauritius which provide in its section 10(4).

  8. La Reforma del Código Penal en Nicaragua

    Directory of Open Access Journals (Sweden)

    María Asunción Moreno Castillo

    2000-08-01

    Full Text Available La redacción de un nuevo Código Penal podría calificarse de urgente necesidad si tenemos en cuenta que nuestras normas penales no se adecuan a las exigencias jurídicas, sociales y políticas de un Estado Social Democrático y de Derecho, pues el Código Penal vigente (1974 no es más que un texto parchado por todas partes, e incluso en alguna ocasión doblemente parchado, que no aguanta más remiendos. De ahí la necesidad de la redacción y aprobación de un texto penal que obedezca a las nuevas tendencias político criminales y postulados del Derecho penal moderno.

  9. LS-SVM: uma nova ferramenta quimiométrica para regressão multivariada. Comparação de modelos de regressão LS-SVM e PLS na quantificação de adulterantes em leite em pó empregando NIR LS-SVM: a new chemometric tool for multivariate regression. Comparison of LS-SVM and pls regression for determination of common adulterants in powdered milk by nir spectroscopy

    Directory of Open Access Journals (Sweden)

    Marco F. Ferrão

    2007-08-01

    Full Text Available Least-squares support vector machines (LS-SVM were used as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants found in powdered milk samples, using near-infrared spectroscopy. Excellent models were built using LS-SVM for determining R², RMSECV and RMSEP values. LS-SVMs show superior performance for quantifying starch, whey and sucrose in powdered milk samples in relation to PLSR. This study shows that it is possible to determine precisely the amount of one and two common adulterants simultaneously in powdered milk samples using LS-SVM and NIR spectra.

  10. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  11. Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

    KAUST Repository

    Chen, Lisha

    2012-12-01

    The reduced-rank regression is an effective method in predicting multiple response variables from the same set of predictor variables. It reduces the number of model parameters and takes advantage of interrelations between the response variables and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group and show that this penalty satisfies certain desirable invariance properties. We develop two numerical algorithms to solve the penalized regression problem and establish the asymptotic consistency of the proposed method. In particular, the manifold structure of the reduced-rank regression coefficient matrix is considered and studied in our theoretical analysis. In our simulation study and real data analysis, the new method is compared with several existing variable selection methods for multivariate regression and exhibits competitive performance in prediction and variable selection. © 2012 American Statistical Association.

  12. Castigo penal, injusticia social y autoridad moral

    Directory of Open Access Journals (Sweden)

    Eduardo Rivera López

    2016-03-01

    Full Text Available La pregunta que exploro en este trabajo es si la injusticia social puede socavar la autoridad moral de la sociedad (y los tribunales para castigar al que delinque. La respuesta a esta pregunta depende esencialmente de cuál sea la teoría justificatoria del castigo penal de la que se parte. Analizo diversas teorías de la pena, entre ellas la teoría consensual de Carlos Nino. Mi objetivo es explorar de qué modo las diferentes teorías de la pena enfrentan el desafío que plantea la pregunta y extraer algunas conclusiones tentativas de ese recorrido.

  13. El concepto de terrorismo en derecho internacional penal

    OpenAIRE

    Valdés Tomàs, Clàudia

    2017-01-01

    Este trabajo consiste en el estudio de la incidencia del concepto de terrorismo en la represión efectiva del delito de terrorismo en el marco del derecho internacional. Por ello, ha sido necesario dividir el trabajo en una primera parte sobre el estudio de la definición del terrorismo en derecho penal internacional y una segunda parte sobre su estudio en derecho internacional penal, específicamente en el contexto de la Corte Penal Internacional (CPI). En la primera parte analizaremos las def...

  14. Lasso and probabilistic inequalities for multivariate point processes

    OpenAIRE

    Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent

    2012-01-01

    Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select coefficients, we propose an adaptive $\\ell_{1}$-penalization methodology, where data-driven weights of the penalty are derived from new Bernstein type inequalities for martingales. Oracle inequalities...

  15. artículo 9 del Código Penal

    Directory of Open Access Journals (Sweden)

    Sebastián Felipe Sánchez Zapata

    2014-01-01

    Full Text Available El artículo 9 del Código Penal colombiano define, como norma rectora del sistema penal, la conducta punible. Este texto, cuestionando la recepción acrítica de doctrinas extranjeras al ordenamiento jurídico (y también códi - gos, normas, etc., expone algunos de los puntos más trascendentales de la teoría del delito, entre ellos, el concepto de conducta, desvalor de acción y re - sultado, relación de causalidad e imputación, ubicación sistemática del dolo y el tratamiento penal de los imputables a través de las interpretaciones de la doctrina penal colombiana.

  16. On the decennium of penal order procedure in Serbia

    Directory of Open Access Journals (Sweden)

    Brkić Snežana

    2011-01-01

    Full Text Available In this paper, the author defines the notion and explains the penal order procedure and its general characteristics. It is one of the special simplified criminal proceedings, which has got special basis and special structure. This procedural form is ultimately aimed at the rationalization of the criminal procedure. It is achieved by avoiding the main hearing in the trial proceeding. The author presents the evolution of the penal order in Serbia from 2001 to 2011. He points to some legal innovations in this field during that decennium. He compares old and new legal provisions about penal order and finds some differences. There is a constant tendency to expanding the area of criminal offences which can be judged in this procedural form. New legal provisions are, in general, better than previous. However, the practice has shown that application of penal order is too small. The previous practice does not live up to expectations of theory and legislator.

  17. La prolusione di rocco e le dottrine del processo penale

    OpenAIRE

    Renzo Orlandi

    2015-01-01

    L’articolo analizza le conseguenze del pensiero giuridico di Arturo Rocco, dal 1910 nella dottrina di procedura penale, ossia, il metodo tecnico-giuridico (esegesi, sistematica e critica). La dogmatica di procedura pena- le inizia con la monografia di Giovanni Conso, nel 1955. L’insoddisfazione con il tecnicismo giuridico e con la mancanza di maturità scientifica si è manifestata con Carnelutti nel 1946 (Cerenterola), sottolineando le peculiarità strutturali del procedimento penale. In questa...

  18. Juridical-penal aspects of the cesium-137 accident

    International Nuclear Information System (INIS)

    Soares, Carolina Chaves

    1997-01-01

    The study of the juridical-penal aspects of the Cesium-137 accident, has, as a base, the police inquiry and the penal lawsuit concerning to the episode. Due to the lack of a law which typified activities related with radioisotope material as crime, the responsible were sentenced according to the penalties of body injury crime and homicide. Among the 10 investigated people, only 5 were condemned by the Judiciary and only 4 serve the sentence. (author)

  19. Performance of Firth-and logF-type penalized methods in risk prediction for small or sparse binary data.

    Science.gov (United States)

    Rahman, M Shafiqur; Sultana, Mahbuba

    2017-02-23

    When developing risk models for binary data with small or sparse data sets, the standard maximum likelihood estimation (MLE) based logistic regression faces several problems including biased or infinite estimate of the regression coefficient and frequent convergence failure of the likelihood due to separation. The problem of separation occurs commonly even if sample size is large but there is sufficient number of strong predictors. In the presence of separation, even if one develops the model, it produces overfitted model with poor predictive performance. Firth-and logF-type penalized regression methods are popular alternative to MLE, particularly for solving separation-problem. Despite the attractive advantages, their use in risk prediction is very limited. This paper evaluated these methods in risk prediction in comparison with MLE and other commonly used penalized methods such as ridge. The predictive performance of the methods was evaluated through assessing calibration, discrimination and overall predictive performance using an extensive simulation study. Further an illustration of the methods were provided using a real data example with low prevalence of outcome. The MLE showed poor performance in risk prediction in small or sparse data sets. All penalized methods offered some improvements in calibration, discrimination and overall predictive performance. Although the Firth-and logF-type methods showed almost equal amount of improvement, Firth-type penalization produces some bias in the average predicted probability, and the amount of bias is even larger than that produced by MLE. Of the logF(1,1) and logF(2,2) penalization, logF(2,2) provides slight bias in the estimate of regression coefficient of binary predictor and logF(1,1) performed better in all aspects. Similarly, ridge performed well in discrimination and overall predictive performance but it often produces underfitted model and has high rate of convergence failure (even the rate is higher than that

  20. A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

    Science.gov (United States)

    Shen, Jianzhao; Gao, Sujuan

    2008-10-01

    In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

  1. A Penalized Likelihood Framework For High-Dimensional Phylogenetic Comparative Methods And An Application To New-World Monkeys Brain Evolution.

    Science.gov (United States)

    Julien, Clavel; Leandro, Aristide; Hélène, Morlon

    2018-06-19

    Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.

  2. Economic viability in concrete dams by multivariable regression tool for implantation of small hydroelectric plants; Viabilidade economica em barragens de concreto pela ferramenta de regressao multivariavel para implantacao de pequenas centrais hidreletrica (PCH)

    Energy Technology Data Exchange (ETDEWEB)

    Lima, Reginaldo Agapito de [Centro Universitario de Itajuba, MG (Brazil)], email: reginaldo_agapito@yahoo.com.br; Ribeiro Junior, Leopoldo Uberto [Voltalia Energia do Brasil, Sao Paulo, SP (Brazil)], email: leopoldo_junior@yahoo.com.br

    2010-07-01

    For implantation of a SHP, the barrage is the main structure where its sizing represents from 30% - 50% of general cost of civil works. Considering this it is very important to have a fast, didactic and accurate tool for elaborating a budget, also allowing a quantitative analysis of inherent cost for civil building of barrages concrete made for small hydropower plants. In face of this, the multi changing regression tool is very important as it allows a fast and correct establishing of preliminary costs, even approximate, for estimates of barrages in concrete cost, enabling to ease the budget, guiding feasibility decisions for selecting or neglecting new alternatives of fall. (author)

  3. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  4. Integrative Analysis of High-throughput Cancer Studies with Contrasted Penalization

    Science.gov (United States)

    Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Shia, BenChang; Ma, Shuangge

    2015-01-01

    In cancer studies with high-throughput genetic and genomic measurements, integrative analysis provides a way to effectively pool and analyze heterogeneous raw data from multiple independent studies and outperforms “classic” meta-analysis and single-dataset analysis. When marker selection is of interest, the genetic basis of multiple datasets can be described using the homogeneity model or the heterogeneity model. In this study, we consider marker selection under the heterogeneity model, which includes the homogeneity model as a special case and can be more flexible. Penalization methods have been developed in the literature for marker selection. This study advances from the published ones by introducing the contrast penalties, which can accommodate the within- and across-dataset structures of covariates/regression coefficients and, by doing so, further improve marker selection performance. Specifically, we develop a penalization method that accommodates the across-dataset structures by smoothing over regression coefficients. An effective iterative algorithm, which calls an inner coordinate descent iteration, is developed. Simulation shows that the proposed method outperforms the benchmark with more accurate marker identification. The analysis of breast cancer and lung cancer prognosis studies with gene expression measurements shows that the proposed method identifies genes different from those using the benchmark and has better prediction performance. PMID:24395534

  5. Introduction to multivariate discrimination

    Science.gov (United States)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  6. Introduction to multivariate discrimination

    International Nuclear Information System (INIS)

    Kegl, B.

    2013-01-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  7. EL TERRORISMO EN EL CÓDIGO PENAL COLOMBIANO

    Directory of Open Access Journals (Sweden)

    Henry Torres Vásquez

    2009-06-01

    Full Text Available En el presente artículo se intenta de manera general abordar el terrorismo desde el punto de vista puramente legal, doctrinal y jurisprudencial. En Colombia es necesario y en ello radica este aporte, generar discusión jurídica respecto a la implementación de los delitos de terrorismo. Aquí se pretende puntualizar los tipos penales nuestros y se estudian algunos aspectos imbricados en los mismos, sin que ello sea un aspecto formal y dogmático, sino que alcontrario, es un análisis a la luz de las actuales interpretaciones sobre el terrorismo, lo cual no obsta para hacer algunos muy breves comentarios al respecto. Los elementos constitutivos de los bienes jurídicos Seguridad Pública y Derecho internacional Humanitario son analizados junto a los ingredientes normativos de los dos tipos penales estipulados en nuestro código penal.

  8. Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

    Science.gov (United States)

    Zhu, Ying; Tan, Tuck Lee

    2016-04-15

    An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

    Science.gov (United States)

    Zhu, Ying; Tan, Tuck Lee

    2016-04-01

    An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

  10. Implementation of a multi-variable regression analysis in the assessment of the generation rate and composition of hospital solid waste for the design of a sustainable management system in developing countries.

    Science.gov (United States)

    Al-Khatib, Issam A; Abu Fkhidah, Ismail; Khatib, Jumana I; Kontogianni, Stamatia

    2016-03-01

    Forecasting of hospital solid waste generation is a critical challenge for future planning. The composition and generation rate of hospital solid waste in hospital units was the field where the proposed methodology of the present article was applied in order to validate the results and secure the outcomes of the management plan in national hospitals. A set of three multiple-variable regression models has been derived for estimating the daily total hospital waste, general hospital waste, and total hazardous waste as a function of number of inpatients, number of total patients, and number of beds. The application of several key indicators and validation procedures indicates the high significance and reliability of the developed models in predicting the hospital solid waste of any hospital. Methodology data were drawn from existent scientific literature. Also, useful raw data were retrieved from international organisations and the investigated hospitals' personnel. The primal generation outcomes are compared with other local hospitals and also with hospitals from other countries. The main outcome, which is the developed model results, are presented and analysed thoroughly. The goal is this model to act as leverage in the discussions among governmental authorities on the implementation of a national plan for safe hospital waste management in Palestine. © The Author(s) 2016.

  11. A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

    Science.gov (United States)

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-01-01

    Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

  12. Responsabilidad penal de las personas jurídicas

    OpenAIRE

    Montes Castro, Claudia Marcela

    2013-01-01

    La responsabilidad penal de las personas jurídicas es un tema que adquiere cada vez mayor relevancia en una sociedad que sufre constantes cambios, y en la que se perfeccionan cada vez más las formas de cometer delitos. En el presente trabajo se realiza el estudio sobre la evolución de la figura de la responsabilidad penal de las personas jurídicas, abarcando desde el derecho romano hasta nuestros días. En el desarrollo del mismo, se expone el recorrido a través de las diferentes alternativas ...

  13. Penalized Maximum Likelihood Estimation for univariate normal mixture distributions

    International Nuclear Information System (INIS)

    Ridolfi, A.; Idier, J.

    2001-01-01

    Due to singularities of the likelihood function, the maximum likelihood approach for the estimation of the parameters of normal mixture models is an acknowledged ill posed optimization problem. Ill posedness is solved by penalizing the likelihood function. In the Bayesian framework, it amounts to incorporating an inverted gamma prior in the likelihood function. A penalized version of the EM algorithm is derived, which is still explicit and which intrinsically assures that the estimates are not singular. Numerical evidence of the latter property is put forward with a test

  14. Funciones del Fiscal en el Sistema Procesal Penal Acusatorio Ecuatoriano

    OpenAIRE

    Guillén, Oscar Medardo

    2006-01-01

    El art.219 de la Constitución Política vigente, define el nuevo marco legal, para el ejercicio de la acción penal de instancia pública, del Ministerio Público, en concordancia con el Nuevo Código de Procedimiento Penal y la Ley Orgánica del Ministerio Público, instrumentos jurídicos que han permitido el cambio del sistema conocido como inquisitivo , caracterizado por la concentración de funciones en el juez, para dar paso al sistema acusatorio oral que se ha dicho es mas humano, democrático y...

  15. Maritime environmental penal law. International and German legislation

    International Nuclear Information System (INIS)

    Eller, Jan Frederik

    2017-01-01

    The book on maritime environmental penal law discusses the following issues: part I: introduction into the importance of oceanic environment and its thread, requirement of protective measures,; part II: focus of the study and terminology: oceanic pollution, maritime environmental legislation, international legislation; part 3: international legislative regulations concerning the protection of maritime environment: avoidance of environmental pollution, maritime legislative agreements, existing protective institutions; part 4: state penal power concerning maritime environmental protection; part 5: statutory offense according to German legislation; perspectives for regulations concerning criminal acts on sea.

  16. MEDIASI PENAL SEBAGAI ALTERNATIF PENYELESAIAN PERKARA PENCURIAN RINGAN (STUDI DI POLRES MALANG KOTA

    Directory of Open Access Journals (Sweden)

    James Hasudungan Hutajulu

    2016-02-01

      Key words: penal mediation, minor theft case, an alternative penal settlement   Abstrak Penelitian mengenai pelaksanaan mediasi penal pada tindak pidana pencurian ringan oleh Polres Malang Kota bertujuan untuk mengetahui dan menganalisis digunakannya mediasi penal serta menganalisis pelaksanaan mediasi penal sebagai alternatif penyelesaian perkara. Adapun metode yang digunakan adalah yuridis sosiologis atau jenis penelitian hukum sosiologis atau penelitian lapangan. Hasil penelitian yang diperoleh antara lain: Polres Malang Kota melakukan mediasi penal dengan alasan agar tercipta rasa keadilan terhadap para saksi sehingga masyarakat puas atas pelayanan yang dilakukan penyidik. Selain itu, langkah-langkah yang dilakukan dalam penerapan mediasi penal ini adalah mempertemukan para pihak, penyidik menyaksikan pengembalian barang yang dicuri oleh pelaku, membantu membuat surat kesepakatan bersama, menerima surat pencabutan perkara serta melakukan gelar perkara.   Kata kunci: mediasi penal, pencurian ringan, alternatif penyelesaian perkara

  17. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  18. Sobre la internacionalización de la justicia penal o el derecho penal como instrumento de guerra

    OpenAIRE

    Ariza Zapata, Daniel

    2009-01-01

    Hablar de Derecho Penal es, sin lugar a dudas, una labor compleja en la medida en que, como suele ser habitual en el ámbito jurídico, no resulta sencillo delimitar su horizonte de proyección. Dado que la ciencia jurídica se expresa por medio de convenciones lingüísticas, de ella pueden predicarse las mismas falencias y dificultades de que adolecen los términos y las palabras, razón suficiente para advertir que, si se quiere abordar un problema esencial del Derecho Penal en cualquier espacio a...

  19. Delincuencia y responsabilidad penal juvenil en Colombia

    Directory of Open Access Journals (Sweden)

    Cristina Montalvo Velásquez

    2011-01-01

    Full Text Available ResumenEl término «delincuencia juvenil» fue acuñado en Inglaterra en el año 1815, “Se entiende por delincuencia juvenil el conjunto de delitos, contravenciones o comportamientos socialmente reprochables, que cometen las personas consideradas como jóvenes por la ley”1 . Cada Estado está sujeto a su propio sistema jurídico, para algunos es delincuente juvenil el adolescente que comete acciones sancionadas por la ley sin importar su gravedad, otros Estados sólo consideran como delincuente juvenil al joven que comete un acto delictivo grave.El fenómeno de la delincuencia juvenil es algo que se inscribe en los espacios de una sociedad en la cual su estructura material, y su formación social consecuente, se halla en una profunda crisis. Que jóvenes conformen bandas de delincuencia organizada nos está indicando que son el resultado de la misma criminalidad general que se ha apoderado de la sociedad en la perspectiva de lograr sobrevivir materialmente. El capitalismo no es sólo acumulación de riqueza sino concentración de la misma en muy pocas manos; y todo el sistema institucional y legal tiende a favorecer ese fenómeno porque éste constituye la supra estructura del modo de producción capitalista. Así como los adultos se organizan para delinquir, lo hacen los niños y los jóvenes a partir de una edad en la cual pueden percibir que la sociedad no es sana y no tienen porvenir humano en ella. Abandonados y sujetos a la violencia que engendra el sistema, ellos simplemente responden en una manifestación de reflejos condicionados que sostienen la sobrevivencia en forma instintiva; “los niños no saben de normas legales sino de formas de sobrevivir a semejante situación; el instinto de sobrevivencia no tiene edades ni la normatividad puede incidir en él”.Palabras ClavesDelincuencia juvenil, Jóvenes, Criminalidad, Familia, Factores, Acto delictivo, Responsabilidad Penal.AbstractThe term “juvenile delinquency” was coined in

  20. Applied multivariate statistics with R

    CERN Document Server

    Zelterman, Daniel

    2015-01-01

    This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the B...

  1. Euthanasia in the Broader Framework of Dutch Penal Policies

    NARCIS (Netherlands)

    Groenhuijsen, M.S.; van Laanen, F.; Groenhuijsen, M.S.; van Laanen, F.

    2006-01-01

    The authors have regarded euthanasia in the broader framework of Dutch penal policies. They present euthanasia as a typical example of the pragmatic - rather than dogmatic - way the Dutch try to tackle difficult moral problems in connection with the criminal justice system. Definitions, statutory

  2. Crime and Punishment: Are Copyright Violators Ever Penalized?

    Science.gov (United States)

    Russell, Carrie

    2004-01-01

    Is there a Web site that keeps track of copyright Infringers and fines? Some colleagues don't believe that copyright violators are ever penalized. This question was asked by a reader in a question and answer column of "School Library Journal". Carrie Russell is the American Library Association's copyright specialist, and she will answer selected…

  3. Making Abortion Safer in Rwanda: Operationalization of the Penal ...

    African Journals Online (AJOL)

    Penal code was revised in Rwanda in 2012 allowing legal termination of pregnancy resulting from rape, incest, forced marriage, or on medical grounds. An evaluation was conducted to assess women's access to abortion services as part of an ongoing program to operationalize the new exemptions for legal abortion.

  4. 27 CFR 24.148 - Penal sums of bonds.

    Science.gov (United States)

    2010-04-01

    ... 27 Alcohol, Tobacco Products and Firearms 1 2010-04-01 2010-04-01 false Penal sums of bonds. 24.148 Section 24.148 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE BUREAU... Vinegar Plant Bond, TTB F 5510.2 Not less than the tax on all wine on hand, in transit, or unaccounted for...

  5. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  6. ANÁLISE CRÍTICA DO DIREITO PENAL DO INIMIGO DE GÜNTHER JAKOBS

    OpenAIRE

    Pilati, Rachel Cardoso

    2009-01-01

    Este artigo tem como objetivo analisar criticamente o Direito Penal do inimigo, verificando sua compatibilidade com o Estado Democrático de Direito e o princípio penal do fato. A primeira parte traz um panorama da política criminal atual no Brasil, situa a teoria do Direito Penal do inimigo nesse contexto, e explica a teoria de Jakobs. No segundo tópico, a teoria de Jakobs é analisada criticamente.Palavras-chave: Direito Penal. Inimigo. Jakobs. Estado Democrático de Direito. Princípio Penal d...

  7. Justicia penal en el Estado arbitrario. La reforma procesal penal durante el nacionalsocialismo, de Javier Llobet Rodríguez

    Directory of Open Access Journals (Sweden)

    Camilo Ernesto Bernal Sarmiento

    2012-09-01

    Full Text Available La obra del profesor Dr. Javier Llobet Rodríguez, catedrático de la Universidad de Costa Rica y abogado litigante, se inserta en una corriente de trabajos surgidos en los últimos diez años en Alemania, España y Latinoamérica relacionados con la identificación del papel que pudieron haber cumplido el derecho penal y la criminología, lo mismo que sus académicos y operadores judiciales, en el proceso de justificación, legitimación formal y aplicación práctica de la barbarie del régimen nacional socialista que lideró Adolf Hitler. En línea de continuidad con sus trabajos de investigación sobre la presunción de inocencia, la detención preventiva y las garantías procesales, Llobet nos propone en Justicia penal en el Estado arbitrario, la reforma procesal penal durante el nacionalsocialismo, analizar la importancia de las garantías del debido proceso estudiando para ello su antítesis, ejemplificada en la actuación meramente policial y la reforma procesal penal que se llevo a cabo durante el nacionalsocialismo   

  8. Criminal responsibility of psychophats in the light of the brazilian penal code Imputabilidade penal dos psicopatas à luz do Código Penal Brasileiro

    Directory of Open Access Journals (Sweden)

    Fernanda Eloise Schmidt Ferreira Feguri

    2012-05-01

    Full Text Available Justifies the choice of this theme, before the controversy in doctrine and jurisprudence as to what a psychopath is being treated before Article 26 § only the Brazilian Penal Code, and also explain why such barbaric crimes in recidivism. At the beginning of the work, it was demonstrated the concept of crime and the disciplines surrounding the criminal law, followed by the concept of a psychopathic, through history, reporting some types of personality disorders, and when and how did the origin of psychopath and how people who had this disorder were treated in the antiquity. It was then explained what becomes of guilt, how takes its implementation, trought accountability, nonimputability sticking to Article 26 § only the Brazilian Penal Code. Following this came to the institute’s measure of security, through its concept, assumptions and methods, including the application, term and termination of dangerousness being still emphasize on expert opinions. Finally, it was reported that cases involving people who have a type of personality disorder, being described succinctly as they are seen to justice and society. Concluding the study, one comes to the conclusion that such individuals are not they amnestied of the semi-liability provided for in Article 26, § only the Brazilian Penal Code Article 26, § only the Brazilian Penal Code. For what can be seen, with latest research is that the benefit of diminished criminal responsibility, given to those agents who do not have full mental unfair, the fact that some people can stay in jail for long as these recourse to psychiatry may be out of hospitals, if any, within three years, by the grace of the laws that protect them. Thus, endorse, this work, that the arrest or other criminal penalty is more honest, more fair, less socially discriminatory, that the sanction psychiatric.Justifica-se a escolha do presente tema, ante a polêmica na doutrina e na jurisprudência, quanto à forma que um psicopata vem

  9. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  10. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  11. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  12. Penal managerialism from within: implications for theory and research.

    Science.gov (United States)

    Cheliotis, Leonidas K

    2006-01-01

    Unlike the bulk of penological scholarship dealing with managerialist reforms, this article calls for greater theoretical and research attention to the often pernicious impact of managerialism on criminal justice professionals. Much in an ideal-typical fashion, light is shed on: the reasons why contemporary penal bureaucracies endeavor systematically to strip criminal justice work of its inherently affective nature; the structural forces that ensure control over officials; the processes by which those forces come into effect; and the human consequences of submission to totalitarian bureaucratic milieus. It is suggested that the heavy preoccupation of present-day penality with the predictability and calculability of outcomes entails the atomization of professionals and the dehumanization of their work. This is achieved through a kaleidoscope of direct and indirect mechanisms that naturalize and/or legitimate acquiescence.

  13. Flexible and efficient genome tiling design with penalized uniqueness score

    Directory of Open Access Journals (Sweden)

    Du Yang

    2012-12-01

    Full Text Available Abstract Background As a powerful tool in whole genome analysis, tiling array has been widely used in the answering of many genomic questions. Now it could also serve as a capture device for the library preparation in the popular high throughput sequencing experiments. Thus, a flexible and efficient tiling array design approach is still needed and could assist in various types and scales of transcriptomic experiment. Results In this paper, we address issues and challenges in designing probes suitable for tiling array applications and targeted sequencing. In particular, we define the penalized uniqueness score, which serves as a controlling criterion to eliminate potential cross-hybridization, and a flexible tiling array design pipeline. Unlike BLAST or simple suffix array based methods, computing and using our uniqueness measurement can be more efficient for large scale design and require less memory. The parameters provided could assist in various types of genomic tiling task. In addition, using both commercial array data and experiment data we show, unlike previously claimed, that palindromic sequence exhibiting relatively lower uniqueness. Conclusions Our proposed penalized uniqueness score could serve as a better indicator for cross hybridization with higher sensitivity and specificity, giving more control of expected array quality. The flexible tiling design algorithm incorporating the penalized uniqueness score was shown to give higher coverage and resolution. The package to calculate the penalized uniqueness score and the described probe selection algorithm are implemented as a Perl program, which is freely available at http://www1.fbn-dummerstorf.de/en/forschung/fbs/fb3/paper/2012-yang-1/OTAD.v1.1.tar.gz.

  14. Environmental penal law - sword of Damocles above public officials?

    International Nuclear Information System (INIS)

    Fuehren, K.H.

    1987-01-01

    An office-holder is subject to punishableness according to art. 324 seq. Penal Code under the same conditions as a citizen. If the office-holder does not intervene in case of environmental delicts, the omission of a required measure is concerned. The constitutional supplement of art. 20 Fundamental Law will have for consequence a further aggravation of the punishableness of office-holders. (CW) [de

  15. A Penalization-Gradient Algorithm for Variational Inequalities

    Directory of Open Access Journals (Sweden)

    Abdellatif Moudafi

    2011-01-01

    Full Text Available This paper is concerned with the study of a penalization-gradient algorithm for solving variational inequalities, namely, find x̅∈C such that 〈Ax̅,y-x̅〉≥0 for all y∈C, where A:H→H is a single-valued operator, C is a closed convex set of a real Hilbert space H. Given Ψ:H→R  ∪  {+∞} which acts as a penalization function with respect to the constraint x̅∈C, and a penalization parameter βk, we consider an algorithm which alternates a proximal step with respect to ∂Ψ and a gradient step with respect to A and reads as xk=(I+λkβk∂Ψ-1(xk-1-λkAxk-1. Under mild hypotheses, we obtain weak convergence for an inverse strongly monotone operator and strong convergence for a Lipschitz continuous and strongly monotone operator. Applications to hierarchical minimization and fixed-point problems are also given and the multivalued case is reached by replacing the multivalued operator by its Yosida approximate which is always Lipschitz continuous.

  16. La justicia del menor: edades penales, realidades y expectativas

    Directory of Open Access Journals (Sweden)

    Félix PANTOJA GARCIA

    1997-01-01

    Full Text Available La ley orgánica 4/92, reguladora de la competencia y el procedimiento de los Juzgados de Menores, otorga al Ministerio Fiscal una serie de competencias que, sin duda alguna, pueden calificarse como de protección de menores. Si bien la ley orgánica referida llene como objetivo establecer un procedimiento para aquellos menores de 16 años y mayores de 12 que han infringido las leyes penales (Código Penal y Leyes Penales especiales y, en consecuencia, expresa el reproche social de sus conductas, no cabe duda de que la pretensión procesal que se desprende de una interpretación sistemática de la Ley es evidentemente educativa, por lo que la responsabilidad atribuida al Fiscal, en cuanto que postula ante el Juzgado la imposición de una medida, es necesariamente protectora. El anteproyecto de Ley de Justicia Juvenil avanza en el camino indicado, y así se manifiesta claramente en su Exposición de Motivos; se trata de “una ley sancionadora de naturaleza primordialmente educativa y no propiamente penal”.

  17. Penal reform in Africa: The case of prison chaplaincy

    Directory of Open Access Journals (Sweden)

    Abraham K. Akih

    2017-08-01

    Full Text Available Penal reform is a challenge across the world. In Africa, those who are incarcerated are especially vulnerable and often deprived of basic human rights. Prison conditions are generally dire, resources are limited, and at times undue force is used to control inmates. The public attitude towards offenders is also not encouraging. Reform efforts include finding alternative ways of sentencing such as community service, making use of halfway houses and reducing sentences. These efforts have not yet yielded the desired results. The four principles of retribution, deterrence, incapacitation and rehabilitation guide penal practice in Africa. Retribution and rehabilitation stand in tension. Deterrence and incapacitation aim at forcing inmates to conform to the social order. The article argues that prison chaplaincy can make a valuable contribution to restoring the dignity and humanity of those who are incarcerated. Chaplaincy can contribute to improving attitudes and practices in the penal system and society. In addition to the social objective of rehabilitation, prison ministry can, on a spiritual level, also facilitate repentance, forgiveness and reconciliation. The aim is the holistic restoration of human beings.

  18. A penalized framework for distributed lag non-linear models.

    Science.gov (United States)

    Gasparrini, Antonio; Scheipl, Fabian; Armstrong, Ben; Kenward, Michael G

    2017-09-01

    Distributed lag non-linear models (DLNMs) are a modelling tool for describing potentially non-linear and delayed dependencies. Here, we illustrate an extension of the DLNM framework through the use of penalized splines within generalized additive models (GAM). This extension offers built-in model selection procedures and the possibility of accommodating assumptions on the shape of the lag structure through specific penalties. In addition, this framework includes, as special cases, simpler models previously proposed for linear relationships (DLMs). Alternative versions of penalized DLNMs are compared with each other and with the standard unpenalized version in a simulation study. Results show that this penalized extension to the DLNM class provides greater flexibility and improved inferential properties. The framework exploits recent theoretical developments of GAMs and is implemented using efficient routines within freely available software. Real-data applications are illustrated through two reproducible examples in time series and survival analysis. © 2017 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.

  19. La prolusione di rocco e le dottrine del processo penale

    Directory of Open Access Journals (Sweden)

    Renzo Orlandi

    2015-03-01

    Full Text Available L’articolo analizza le conseguenze del pensiero giuridico di Arturo Rocco, dal 1910 nella dottrina di procedura penale, ossia, il metodo tecnico-giuridico (esegesi, sistematica e critica. La dogmatica di procedura pena- le inizia con la monografia di Giovanni Conso, nel 1955. L’insoddisfazione con il tecnicismo giuridico e con la mancanza di maturità scientifica si è manifestata con Carnelutti nel 1946 (Cerenterola, sottolineando le peculiarità strutturali del procedimento penale. In questa prospettiva, il testo sottolinea la conferenza di Franco Cordero nel 1964 (Lecce, così come le lezioni da James Goldschmidt. Inoltre, negli anni sessanta, divennero importanti diritti fondamentali, di fronte alla Costituzione democratica, con un nuovo orientamento dottrinale. Il diritto processuale penale è stato considerato come diritto costituzionale applicato. Si segnalano gli insegnamenti di Amodio, Amato, Chiavario, Ferrua, Grevi, Iluminati, Massa e Nobili. Successivamente, l’articolo mette in evidenza il CPP del 1988, l’internazionalizzazione dei sistemi giuridici, l’importanza del diritto comparato e dei diritti fondamentali. Si conclude con il nuovo ordine mondiale dei diplomi internazionali e tribunali sovranazionali, con nuove esigenze, oltre il tecnicismo giuridico.

  20. Garantismo penal para quem? O discurso penal liberal drente à sua desconstrução pela criminologia

    Directory of Open Access Journals (Sweden)

    Marisa Helena D`Arbo Alves de Freitas

    2017-05-01

    Full Text Available http://dx.doi.org/10.5007/2177-7055.2017v38n75p129 O presente artigo versa sobre a efetividade das garantias individuais e o reflexo dessa problemática no acesso à justiça penal brasileira. Apesar de o discurso idealista-garantista apresentar os instrumentos possíveis para defesa dos acusados e para isonomia de tratamento aos sujeitos do processo, a realidade processual indica que esse discurso é meramente retórico e limitado ao plano teórico-abstrato, com dificuldades de se concretizar no plano prático-reformista. O trabalho é bibliográfico e desenvolve conceitos relativos à seletividade e as formas de controle do poder punitivo. Para abordagem do tema, partiu-se da perspectiva crítica do garantismo penal proposto por Luigi Ferrajoli.

  1. LA CARGA DINÁMICA PROBATORIA Y SU REPERCUSIÓN EN EL PROCESO PENAL DESDE LAS REGLAS DE MALLORCA Y LA TEORÍA DEL GARANTISMO PENAL

    Directory of Open Access Journals (Sweden)

    Sebastián Betancourt Restrepo

    2010-01-01

    Full Text Available El presente artículo pretende hacer algunos cuestionamientos en torno a la implementación de la teoría de la carga dinámica de la prueba en la actuación penal, a partir de los elementos brindados por las Reglas de Mallorca y la teoría del garantismo penal, defendida por el profesor Luigi Ferrajoli en Italia, y en Argentina por el profesor Adolfo Alvarado Velloso, desde la perspectiva de una sistemática procesal penal, reconocedora de garantías universales como el debido proceso.

  2. LA CARGA DINÁMICA PROBATORIA Y SU REPERCUSIÓN EN EL PROCESO PENAL DESDE LAS REGLAS DE MALLORCA Y LA TEORÍA DEL GARANTISMO PENAL

    OpenAIRE

    Sebastián Betancourt Restrepo

    2010-01-01

    El presente artículo pretende hacer algunos cuestionamientos en torno a la implementación de la teoría de la carga dinámica de la prueba en la actuación penal, a partir de los elementos brindados por las Reglas de Mallorca y la teoría del garantismo penal, defendida por el profesor Luigi Ferrajoli en Italia, y en Argentina por el profesor Adolfo Alvarado Velloso, desde la perspectiva de una sistemática procesal penal, reconocedora de garantías universales como el debido proceso.

  3. Continuous multivariate exponential extension

    International Nuclear Information System (INIS)

    Block, H.W.

    1975-01-01

    The Freund-Weinman multivariate exponential extension is generalized to the case of nonidentically distributed marginal distributions. A fatal shock model is given for the resulting distribution. Results in the bivariate case and the concept of constant multivariate hazard rate lead to a continuous distribution related to the multivariate exponential distribution (MVE) of Marshall and Olkin. This distribution is shown to be a special case of the extended Freund-Weinman distribution. A generalization of the bivariate model of Proschan and Sullo leads to a distribution which contains both the extended Freund-Weinman distribution and the MVE

  4. Methods of Multivariate Analysis

    CERN Document Server

    Rencher, Alvin C

    2012-01-01

    Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit

  5. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  6. Arte y derecho penal: El caso Han Van Meegeren

    Directory of Open Access Journals (Sweden)

    Ricardo Medina Moyano

    1968-01-01

    Full Text Available La temática que abarcan las palabras que sirven de título a estas notas, es ciertamente de inasible amplitud, ya por lo proteíco de la conducta humana, de quienes se colocan al margen de la ley, ora por la riqueza inconmensurable del fenómeno estético. Cabría, pues, en primer término, plantear como hipótesis de trabajo, los muy diversos enfoques desde los cuales sería dable la investigación de las relaciones entre el Arte y el Derecho Penal.

  7. Debido proceso, sistemas y reforma del proceso penal

    Directory of Open Access Journals (Sweden)

    Teresa Armenta Deu

    2015-03-01

    Full Text Available Este artículo se propone examinar los modelos de procesos penales de los movimientos de reforma que se establecieron en las últimas décadas del siglo XX, en los países iberoamericanos. Para ello, primero se enfatiza las características históricas de cada sistema, poniendo de relieve la importancia de no confundir el acusatorio con el adversarial, rechazando la coincidencia entre los sistemas actuales y mixto inquisitivo histórico. Apoya la importancia de la igualdad de armas y e del contradictoria en la búsqueda de un equilibrio entre los modelos de procedimiento.

  8. Comparing implementations of penalized weighted least-squares sinogram restoration

    International Nuclear Information System (INIS)

    Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick

    2010-01-01

    Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix

  9. Imprudencia inconsciente y derecho penal de la culpabilidad

    OpenAIRE

    Guanais de Aguiar Filho, Oliveiros

    2016-01-01

    La discusión sobre la compatibilidad entre la imprudencia inconsciente y el principio de culpabilidad ha llamado la atención de la dogmática penal hace más de dos siglos. La primera parte de este trabajo presenta esta polémica histórica de forma crítica desde Feuerbach y sus contemporáneos hasta el finalismo. En la segunda parte del trabajo se tienen en cuenta las críticas a la imprudencia inconsciente y se analizan los fundamentos de esta modalidad de imputación bajo la perspectiva de la teo...

  10. Multivariate GARCH models

    DEFF Research Database (Denmark)

    Silvennoinen, Annastiina; Teräsvirta, Timo

    This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes nonparametric and semiparametric models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example...

  11. Multivariate Time Series Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  12. Estimation and model selection of semiparametric multivariate survival functions under general censorship.

    Science.gov (United States)

    Chen, Xiaohong; Fan, Yanqin; Pouzo, Demian; Ying, Zhiliang

    2010-07-01

    We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root- n asymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.

  13. Mortality of persons deprived of liberty in the penal system

    Directory of Open Access Journals (Sweden)

    Jovanić Goran

    2016-01-01

    Full Text Available The main aim of this research is to determine the scope, dynamics, and structure of deaths of persons deprived of their liberty who resided in the penal system due to custody, security measures, serving a prison sentence or an alternative sanction, with regard to their demographic, criminological, penal, and psychological characteristics. Article 111, paragraph b of the United Nations Rules for the Protection of Juveniles Deprived of their Liberty (1990 determines that deprivation of liberty refers to any kind of detention, imprisonment, i.e. placement in a public or private institution which the imprisoned person cannot leave, by order of judicial, administrative or other public authority. The data used included information on persons deprived of their liberty who died in the territory of the Republic of Serbia in the period from 2008 to 2012. The data was obtained from The Directorate for Execution of Criminal Sanctions of the Ministry of Justice of the Republic of Serbia. In the past, researches mainly focused on violence in prisons, death penalty, prison riots, auto-aggressive behavior, i.e. certain forms of mortality such as a suicide. This paper aims to point out the characteristics of deaths which occur while persons deprived of their liberty are under the authority of judicial institutions, both before and after passing a criminal sanction.

  14. The development of the penal system in Serbian criminal law

    Directory of Open Access Journals (Sweden)

    Jakšić Dušan

    2013-01-01

    Full Text Available The continuous development of the penal system in Serbia is reflected in significant changes within the criminal legislative solutions. The most important legal document of the medieval Serbia, 'Dušan's Code' was characterized by harsh corporal and death punishments taken from the Byzantine law. During the Ottoman period 'Dušan's Code' was no longer in use, and with the beginning of the First Serbian Uprising, the adoption of individual legislations began. The Criminal Code of the Principality of Serbia, adopted in 1860, introduced a novelty of major and minor penalties, including, most importantly, several types of detention. The Criminal Code of the Kingdom of Yugoslavia was adopted in 1929 and it predicted different types of sanctions other than fines. The main feature of the Criminal Code of the Kingdom of Yugoslavia was permanent abolition of the corporal punishment. After the Second World War, the newly formed government adopted new criminal codes and new forms of punishment, which remained unchanged from the Novel in 1959 up until the dissolution of the SFRY. Contemporary criminal legislation of the Republic of Serbia is characterized by the abolition of the death penalty, seizure of property and the introduction of new penalties, which should, instead of short prison sentences, serve as an alternative. Throughout its statehood, from the Middle Ages up until today, Serbia has always had a continuity of the penal system development parallel with its development, primarily in Europe.

  15. Integrative Analysis of Cancer Diagnosis Studies with Composite Penalization

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2013-01-01

    Summary In cancer diagnosis studies, high-throughput gene profiling has been extensively conducted, searching for genes whose expressions may serve as markers. Data generated from such studies have the “large d, small n” feature, with the number of genes profiled much larger than the sample size. Penalization has been extensively adopted for simultaneous estimation and marker selection. Because of small sample sizes, markers identified from the analysis of single datasets can be unsatisfactory. A cost-effective remedy is to conduct integrative analysis of multiple heterogeneous datasets. In this article, we investigate composite penalization methods for estimation and marker selection in integrative analysis. The proposed methods use the minimax concave penalty (MCP) as the outer penalty. Under the homogeneity model, the ridge penalty is adopted as the inner penalty. Under the heterogeneity model, the Lasso penalty and MCP are adopted as the inner penalty. Effective computational algorithms based on coordinate descent are developed. Numerical studies, including simulation and analysis of practical cancer datasets, show satisfactory performance of the proposed methods. PMID:24578589

  16. The penal aspect of the essence of the legal institute

    Directory of Open Access Journals (Sweden)

    Олег Миколайович Кревсун

    2016-04-01

    Full Text Available Law, like any social phenomenon, can be the object of cognition only if legal norms that is its components, will come into connection with other legal norms, not only to form separate elements of the law. Without a comprehensive study of the interaction between legal norms, their role in the regulation of social relations will be impossible to develop effective legal measures of influence on various spheres of public life. Unfortunately, proper attention to this issue in Ukraine is not given. Examined, in fact, a certain set of interconnected rules of law, but each of them, representing this population, is investigated separately, without necessary connection with other laws. However, as presented in the legal literature, the research results confirmed the existence in law of such legal norms, which are involved in the regulation of certain social relations, being in its totality as an integrated whole. Such laws called legal institutions. Legal institutions, subinstitutes and interdisciplinary subinstitutes of penal law, both from the point of view of legal terminology and from the point of view of defining the content, in domestic science remains thoroughly unexplored and only mentioned in some scientific works of foreign authors. The term “legal institution” is used by scholars more as a term authoritative sound. In this article, we first provide a definition of the legal Institute, subinstitute and cross-subinstitute of penal law, interpret the normative contents of the allocated inherent characteristics, focusing on the absence in domestic science studies on this issue.

  17. Os indesejáveis no Direito Penal moderno

    Directory of Open Access Journals (Sweden)

    Patrícia Graziela Gonçalves

    2010-02-01

    Full Text Available

    Este trabalho propõe a fazer uma breve aborfagem da obra "O inimigo no Direito Penal", de Eugênio Raul Zafforni, um dos maiores penalistas da América Latina. Neste obra, o autor ressalta que o poder punitivo sempre classificou e reconheceu um hostis, um estranho ou indesejável, sobre o qual se aplicou um tratamento discriminatório, neutralizante e eliminatório, negando-lhe a sua condição de pessoa e considerando-o em função da sua condição de coisa ou ente perigoso. E mais, tanto as leis quanto a doutrina legitimam esse tratamento, baseadas em saberes pretensamente empíricos sobre a conduta humana. Tal doutrina-penal contradiz os princípios constitucionais do Estado de Direito e mais se aproxima do modelo de Estado absoluto.

  18. A Penalization Approach for Tomographic Reconstruction of Binary Axially Symmetric Objects

    International Nuclear Information System (INIS)

    Abraham, R.; Bergounioux, M.; Trelat, E.

    2008-01-01

    We propose a variational method for tomographic reconstruction of blurred and noised binary images based on a penalization process of a minimization problem settled in the space of bounded variation functions. We prove existence and/or uniqueness results and derive a penalized optimality system. Numerical simulations are provided to demonstrate the relevance of the approach

  19. Incorporation of punishable offences against the law on protection of the environment into the penal code

    International Nuclear Information System (INIS)

    Moehrenschlager, M.

    1979-01-01

    The government bill on the sixteenth act amending the penal legislation - act on the prevention of environmental offences - is presented, with comments being given on the most important stipulations. Paragraph 328 of the penal code deals with the unauthorized handling of nuclear fuels and represents an almost complete adoption of Paragraph 45 of the Atomic Energy law. The prohibition of the operation of nuclear facilities laid down in Paragraph 45, par. 1, No.4 of the Atomic Energy law, has been incorporated into the factural characteristics of illegal operation of facilities (Paragraph 327, par. 1,3 No. 1 of the penal code). The illegal handling of other radioactive substances has been dealt with in regard to some important cases: specifically for the case of illegal waste disposal (Paragraph 326, par. 1 No. 2, par. 2 of the penal code), and for the case of irregular transport leading to concrete danger or nuisance (Paragraph 330, par. 1 No. 4 of the penal code), as well as for the case of release of ionizing radiation having any such consequences (Paragraph 330, par. 1 No. 2, item c of the penal code). According to Paragraph 324 of the penal code, radioactive contamination of waters is a punishable offence. The rule of qualification of Paragraph 330 par. 1 of the penal code is to be applied to all these facts. (orig./HP) 891 HP/orig.- 892 MB [de

  20. A penalization approach to linear programming duality with application to capacity constrained transport

    OpenAIRE

    Korman, Jonathan; McCann, Robert J.; Seis, Christian

    2013-01-01

    A new approach to linear programming duality is proposed which relies on quadratic penalization, so that the relation between solutions to the penalized primal and dual problems becomes affine. This yields a new proof of Levin's duality theorem for capacity-constrained optimal transport as an infinite-dimensional application.

  1. Penal stress and its manifestations in the convicts, suspects and accused persons

    Directory of Open Access Journals (Sweden)

    Melnikova D.V.

    2015-08-01

    Full Text Available The paper is devoted to penal stress and its manifestations at the convicts, suspects and accused persons. This topic has been poorly studied. It is necessary to identify the groups of people especially most in need of prevention and correction of stress state and to define the target effects. The paper presents a theoretical analysis of the concepts of biological and psychological stress. Our theoretical work is mainly devoted to phenomenon of penal stress and factors affecting its formation. We suggested the definition of penal stress concept on the basis of the analyzed literature. The sample included 69 male persons (31 from predetention center, 38 from penal colony, aged 19 to 47 years old. Experimental psychological method of research was mainly used. In the practical part of the paper presents data on the prevalence of the penal stress in predetention centers and penal colonies. In addition, we have studied the relationship of penal stress with punishment stage, the crime characteristics of subjects, individual psychological characteristics, current state. The study allows us to reveal the groups of people in need of the prevention and correction of the penal stress state. We identified some target corrective action also.

  2. A MULTIVARIATE ANALYSIS OF CROATIAN COUNTIES ENTREPRENEURSHIP

    Directory of Open Access Journals (Sweden)

    Elza Jurun

    2012-12-01

    Full Text Available In the focus of this paper is a multivariate analysis of Croatian Counties entrepreneurship. Complete data base available by official statistic institutions at national and regional level is used. Modern econometric methodology starting from a comparative analysis via multiple regression to multivariate cluster analysis is carried out as well as the analysis of successful or inefficacious entrepreneurship measured by indicators of efficiency, profitability and productivity. Time horizons of the comparative analysis are in 2004 and 2010. Accelerators of socio-economic development - number of entrepreneur investors, investment in fixed assets and current assets ratio in multiple regression model are analytically filtered between twenty-six independent variables as variables of the dominant influence on GDP per capita in 2010 as dependent variable. Results of multivariate cluster analysis of twentyone Croatian Counties are interpreted also in the sense of three Croatian NUTS 2 regions according to European nomenclature of regional territorial division of Croatia.

  3. Localismo e non-neutralità culturale del diritto penale ‘sotto tensione’ per effetto dell’immigrazione

    Directory of Open Access Journals (Sweden)

    Fabio Basile

    2011-05-01

    penale: “il diritto penale è fortemente impregnato di cultura”. - 3. Conclusioni: le implicazioni di ‘localismo’ e ‘non-neutralità culturale’ del diritto penale in ordine al fenomeno dei reati ‘culturalmente motivati’ commessi dagli immigrati.

  4. Multivariate Birkhoff interpolation

    CERN Document Server

    Lorentz, Rudolph A

    1992-01-01

    The subject of this book is Lagrange, Hermite and Birkhoff (lacunary Hermite) interpolation by multivariate algebraic polynomials. It unifies and extends a new algorithmic approach to this subject which was introduced and developed by G.G. Lorentz and the author. One particularly interesting feature of this algorithmic approach is that it obviates the necessity of finding a formula for the Vandermonde determinant of a multivariate interpolation in order to determine its regularity (which formulas are practically unknown anyways) by determining the regularity through simple geometric manipulations in the Euclidean space. Although interpolation is a classical problem, it is surprising how little is known about its basic properties in the multivariate case. The book therefore starts by exploring its fundamental properties and its limitations. The main part of the book is devoted to a complete and detailed elaboration of the new technique. A chapter with an extensive selection of finite elements follows as well a...

  5. Applied multivariate statistical analysis

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

  6. Directional quantile regression in R

    Czech Academy of Sciences Publication Activity Database

    Boček, Pavel; Šiman, Miroslav

    2017-01-01

    Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

  7. A MULTIVARIATE WEIBULL DISTRIBUTION

    Directory of Open Access Journals (Sweden)

    Cheng Lee

    2010-07-01

    Full Text Available A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu and Bhattacharyya. From the survival function, the probability density function, the cumulative probability function, the determinant of the Jacobian Matrix, and the general moment are derived.

  8. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  9. Multivariate data analysis

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set...

  10. Multivariate pattern dependence.

    Directory of Open Access Journals (Sweden)

    Stefano Anzellotti

    2017-11-01

    Full Text Available When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD: a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS and to the fusiform face area (FFA, using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.

  11. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. Sistema de atribución de responsabilidad penal a las personas jurídicas

    OpenAIRE

    Pérez Arias, Jacinto

    2013-01-01

    La presente tesis aborda el análisis del modelo de atribución de responsabilidad penal de las personas jurídica en el ordenamiento jurídico español, establecido mediante LO 5/2010 de Reforma del Código Penal. Además de unas breves notas sobre la evolución legislativa, histórica y de derecho comparado, se estudian los problemas mas relevantes de la responsabilidad penal corporativa, como la incapacidad de acción y culpabilidad de la persona jurídica, aspectos diferenciadores entre el derecho a...

  13. Las negociaciones en el proceso penal: del procedimiento inquisitivo a la prisionización masiva

    Directory of Open Access Journals (Sweden)

    Julio César Montañez Ruiz

    2013-12-01

    Full Text Available La presente investigación plantea la problemática de la prisionización masiva que generan las negociaciones en el sistema procesal penal de tendencia acusatoria, con marcada influencia norteamericana; aquí se sostiene que ese mecanismo, mediante el cual la Fiscalía busca la declaratoria masiva de culpabilidad de los imputados en plan de descongestionar el sistema represivo penal, tiene las caraterísticas más inquisitivas de un sistema de enjuiciamiento penal.

  14. Domestic violence and Special Criminal Courts: analysis from the legal feminism and penal criticism perspectives

    OpenAIRE

    Campos, Carmen Hein de; Carvalho, Salo de

    2006-01-01

    Este artigo pretende demonstrar a possibilidade de análise crítica da Lei 9.099/95 a partir de dois discursos considerados marginais no campo do direito penal: o feminismo jurídico e o garantismo penal. Considerando a vítima no momento do crime e o autor do fato durante o processo penal, esses discursos interagem, procurando construir um diálogo para demonstrar a ineficácia da lei em ambas as perspectivas.This article aims at demonstrating the possibility of criticism about the criminal law (...

  15. Direito penal na era global: garantismo positivo ajustado ao garantismo negativo

    OpenAIRE

    Gomes, Thiago Quintas

    2009-01-01

    Esta dissertação faz análise da complexa sociedade do pós-industrial, hedonista, de massa e relações objetivas, denominada sociedade de risco, e qual deve ser a postura do direito penal diante dos novos interesses, difusos e coletivos, de um mundo globalizado. O direito penal deve estar preparado para lidar com esta nova realidade, o que significa a adoção de uma nova dogmática jurídica-penal na proteção dos bens meta-individuais (direitos humanos de 3ª dimensão), porém conformada com o...

  16. Cooperación internacional en materia penal en el MERCOSUR: el cibercrimen

    OpenAIRE

    Santiago Deluca; Enrique Del Carril

    2017-01-01

    En el Mercosur no existe un derecho penal común, no obstante observarse una creciente corriente orientada a la adopción de normas generales de política criminal tendiente a combatir diversos actos delictivos. Ello se cristaliza en la creación de normas de cooperación internacional en materia penal, con el objeto de lograr la asimilación y adecuación “macro” de las legislaciones penales de los Estados Parte. Es justo reconocer que en este trabajo no se pretende elaborar un corpus iuris por ...

  17. Prime note sulla tutela penale dei culti nei Paesi dell’Est Europa

    Directory of Open Access Journals (Sweden)

    Giovanni Cimbalo

    2011-05-01

    Full Text Available Testo della relazione tenuta al Convegno “La Carta e la Corte” (Ferrara, 27 ottobre 2007 destinata alla pubblicazione negli Atti. SOMMARIO: 1. Alcune considerazioni preliminari sullo status delle Confessioni religiose nei paesi dell’Est Europa - 2. I nuovi orientamenti del diritto penale nell’Est Europa - 3. Le norme statali in materia di tutela penale dei culti e del sentimento religioso. 3. Le norme penali relative ai culti e a al sentimento religioso prima del 1992 nei Paesi dell’Est Europa - 4. Tipologie e tecniche legislative di tutela penale dei culti dopo il 1992 nei Paesi dell’Est Europa - 5. Alcune sommarie considerazioni.

  18. Cultura Política republicana e o Código Penal de 1890 * Cultura Política republicana y el Código Penal de 1890

    Directory of Open Access Journals (Sweden)

    PAULO HENRIQUE MIOTTO DONADELI

    2014-12-01

    Full Text Available Resumo: O presente artigo buscar estabelecer o conceito de Cultura Política, para compreender a dinâmica da Cultura Política Republicana que se instaurou no Brasil no final do século XIX, como meio de analisar as novas tendências penais da Primeira República (1889-1930, que se codificam no Código Penal de 1890. Ao analisar as condições e contradições desse diploma penal, o artigo convida a fazer uma reflexão sobre a sociedade da época, mostrando que a lei penal é o resultado dos interesses e conflitos que permeia a implantação e consolidação de uma cultural política republicana. A tese central do artigo é mostrar que a elite republicana aproveitou das concepções penais para implantar e justificar mecanismos de repressão e de controle do crime, como uma das formas de dominação e manutenção de poder.Palavras-chave: Cultura Política; República Velha; Direito Penal.Resumen: En este trabajo se busca establecer el concepto de cultura política, para entender la dinámica de la cultura política republicana en Brasil que surgieron a finales del siglo XIX, como una forma de analizar las nuevas tendencias criminales de la Primera República (1889-1930, que están codificadas en el Código Penal de 1890. Al analizar las condiciones y contradicciones de esta ley penal, el artículo llama a una reflexión sobre la sociedad de la época, lo que demuestra que el derecho penal es el resultado de intereses y conflictos que se respira en la implementación y consolidación de una cultura política republicana. La tesis central del artículo es mostrar que la élite republicana aprovechó concepciones penales para implementar y justificar los mecanismos de represión y control de la delincuencia, como una forma de dominación y mantenimiento del poder.Palabras clave: Cultura Política; República Vieja; Derecho Penal.

  19. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng

    2013-11-05

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  20. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

    2013-01-01

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  1. Multivariate wavelet frames

    CERN Document Server

    Skopina, Maria; Protasov, Vladimir

    2016-01-01

    This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...

  2. Multivariate calculus and geometry

    CERN Document Server

    Dineen, Seán

    2014-01-01

    Multivariate calculus can be understood best by combining geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. This textbook has successfully followed this programme. It additionally provides a solid description of the basic concepts, via familiar examples, which are then tested in technically demanding situations. In this new edition the introductory chapter and two of the chapters on the geometry of surfaces have been revised. Some exercises have been replaced and others provided with expanded solutions. Familiarity with partial derivatives and a course in linear algebra are essential prerequisites for readers of this book. Multivariate Calculus and Geometry is aimed primarily at higher level undergraduates in the mathematical sciences. The inclusion of many practical examples involving problems of several variables will appeal to mathematics, science and engineering students.

  3. Intelligent multivariate process supervision

    International Nuclear Information System (INIS)

    Visuri, Pertti.

    1986-01-01

    This thesis addresses the difficulties encountered in managing large amounts of data in supervisory control of complex systems. Some previous alarm and disturbance analysis concepts are reviewed and a method for improving the supervision of complex systems is presented. The method, called multivariate supervision, is based on adding low level intelligence to the process control system. By using several measured variables linked together by means of deductive logic, the system can take into account the overall state of the supervised system. Thus, it can present to the operators fewer messages with higher information content than the conventional control systems which are based on independent processing of each variable. In addition, the multivariate method contains a special information presentation concept for improving the man-machine interface. (author)

  4. Multivariate rational data fitting

    Science.gov (United States)

    Cuyt, Annie; Verdonk, Brigitte

    1992-12-01

    Sections 1 and 2 discuss the advantages of an object-oriented implementation combined with higher floating-point arithmetic, of the algorithms available for multivariate data fitting using rational functions. Section 1 will in particular explain what we mean by "higher arithmetic". Section 2 will concentrate on the concepts of "object orientation". In sections 3 and 4 we shall describe the generality of the data structure that can be dealt with: due to some new results virtually every data set is acceptable right now, with possible coalescence of coordinates or points. In order to solve the multivariate rational interpolation problem the data sets are fed to different algorithms depending on the structure of the interpolation points in then-variate space.

  5. Transient multivariable sensor evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Vilim, Richard B.; Heifetz, Alexander

    2017-02-21

    A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.

  6. Determination of sulfamethoxazole and trimethoprim mixtures by multivariate electronic spectroscopy

    OpenAIRE

    Cordeiro, Gilcélia A.; Peralta-Zamora, Patricio; Nagata, Noemi; Pontarollo, Roberto

    2008-01-01

    In this work a multivariate spectroscopic methodology is proposed for quantitative determination of sulfamethoxazole and trimethoprim in pharmaceutical associations. The multivariate model was developed by partial least-squares regression, using twenty synthetic mixtures and the spectral region between 190 and 350 nm. In the validation stage, which involved the analysis of five synthetic mixtures, prediction errors lower that 3% were observed. The predictive capacity of the multivariate model...

  7. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  8. Canonical variate regression.

    Science.gov (United States)

    Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

    2016-07-01

    In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  9. La protección penal del medio ambiente. Análisis del art. 338 del Código Penal colombiano sobre minería ilegal

    Directory of Open Access Journals (Sweden)

    Sebastián Felipe Sánchez Zapata

    2016-03-01

    Full Text Available El estudio de la criminalidad medio-ambiental comprende todo un elenco de problemas jurídico-penales de muy difícil solución. Basta acudir a las dificultades que sobresalen al momento de definir el bien jurídico protegido, el desvalor de acción y resultado, las leyes penales en blanco, la relación de causalidad, etc. Un acercamiento, aunque sea superficial, a las dificultades ínsitas de estas categorías revela el uso que se está dando, en nuestro contexto, a la retórica apuesta del legislador por proteger concretos objetos materiales como los yacimientos mineros, las aguas y el material de arrastre. El texto, desde una perspectiva penal, expone la realidad de la  minería ilegal en Colombia y las formas institucionales de reacción contra ella.

  10. A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood

    KAUST Repository

    Lee, Seokho; Huang, Jianhua Z.

    2013-01-01

    We propose a new biclustering method for binary data matrices using the maximum penalized Bernoulli likelihood estimation. Our method applies a multi-layer model defined on the logits of the success probabilities, where each layer represents a

  11. A eutanásia na visão do garantismo penal

    OpenAIRE

    Reicher, Regina Maria

    2005-01-01

    Num cotejo entre a eutanásia e o garantismo de Luigi Ferrajoli, quanto à proibição penal, os princípios da lesividade e necessidade, e o direito penal mínimo, este estudo faz uma projeção sobre as principais conseqüências desse comportamento em matéria penal, notadamente quanto à sua repercussão sobre o princípio da dignidade da pessoa humana, que é corolário lógico do Estado Democrático de Direito. Não se justifica, no modelo de direito penal mínimo propugnado pelo garantismo, a penalizaç...

  12. Control Multivariable por Desacoplo

    Directory of Open Access Journals (Sweden)

    Fernando Morilla

    2013-01-01

    Full Text Available Resumen: La interacción entre variables es una característica inherente de los procesos multivariables, que dificulta su operación y el diseño de sus sistemas de control. Bajo el paradigma de Control por desacoplo se agrupan un conjunto de metodologías, que tradicionalmente han estado orientadas a eliminar o reducir la interacción, y que recientemente algunos investigadores han reorientado con objetivos de solucionar un problema tan complejo como es el control multivariable. Parte del material descrito en este artículo es bien conocido en el campo del control de procesos, pero la mayor parte de él son resultados de varios años de investigación de los autores en los que han primado la generalización del problema, la búsqueda de soluciones de fácil implementación y la combinación de bloques elementales de control PID. Esta conjunción de intereses provoca que no siempre se pueda conseguir un desacoplo perfecto, pero que sí se pueda conseguir una considerable reducción de la interacción en el nivel básico de la pirámide de control, en beneficio de otros sistemas de control que ocupan niveles jerárquicos superiores. El artículo resume todos los aspectos básicos del Control por desacoplo y su aplicación a dos procesos representativos: una planta experimental de cuatro tanques acoplados y un modelo 4×4 de un sistema experimental de calefacción, ventilación y aire acondicionado. Abstract: The interaction between variables is inherent in multivariable processes and this fact may complicate their operation and control system design. Under the paradigm of decoupling control, several methodologies that traditionally have been addressed to cancel or reduce the interactions are gathered. Recently, this approach has been reoriented by several researchers with the aim to solve such a complex problem as the multivariable control. Parts of the material in this work are well known in the process control field; however, most of them are

  13. Responsabilidades en Prevención de riesgos laborales; Especial referencia a la responsabilidad penal

    OpenAIRE

    Fernández Fernández, Cristina

    2012-01-01

    En este proyecto fin de grado se abordan las responsabilidades empresariales de prevención de riesgos laborales; civiles, administrativos, penales y recargo de prestaciones por incumplimiento de la normativa de prevención de riesgos laborales, con referencias jurisprudenciales y normativa vigente. Se hace especial referencia a la responsabilidad penal detallando los distintos tipos de delito; de peligro y de resultado, con sus distintas modalidades dolosa e imprudente, en su...

  14. Transfrontier environmental protection and German penal law. Grenzueberschreitende Umweltbelastungen und deutsches Strafrecht

    Energy Technology Data Exchange (ETDEWEB)

    Forkel, H.W.

    1988-01-22

    The author investigates the problem of how far German penal law is valid in case of transfrontier environmental pollution. He distinguishes between cases in which the interests of Germany and the neighbour state are congruent, and cases in which they are not congruent. According to the author, German law should be applied in cases where the other country has no environmental penal legislation, and where the emissions exceed the limits set by German and foreign law. (orig./HSCH).

  15. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  16. Prácticas de control socio-penal dispositivo psi pericial y adolescentes mujeres en el Sistema Penal Juvenil Uruguayo /

    OpenAIRE

    López Gallego, Laura

    2016-01-01

    La presente tesis doctoral "Prácticas de Control Socio-Penal. Dispositivo Psi Pericial y Adolescentes Mujeres en el Sistema Penal Juvenil Uruguayo" se sitúa en una perspectiva analítica que articula postulados de la Psicología Social Crítica y las Epistemologías Feministas, junto con aportes criminológicos provenientes de la Criminología Crítica y la Criminología Feminista. Los itinerarios de investigación producidos en esta tesis doctoral se descomponen en dos proyectos de investigación. Uno...

  17. Precision Index in the Multivariate Context

    Czech Academy of Sciences Publication Activity Database

    Šiman, Miroslav

    2014-01-01

    Roč. 43, č. 2 (2014), s. 377-387 ISSN 0361-0926 R&D Projects: GA MŠk(CZ) 1M06047 Institutional support: RVO:67985556 Keywords : data depth * multivariate quantile * process capability index * precision index * regression quantile Subject RIV: BA - General Mathematics Impact factor: 0.274, year: 2014 http://library.utia.cas.cz/separaty/2014/SI/siman-0425059.pdf

  18. Multitask Quantile Regression under the Transnormal Model.

    Science.gov (United States)

    Fan, Jianqing; Xue, Lingzhou; Zou, Hui

    2016-01-01

    We consider estimating multi-task quantile regression under the transnormal model, with focus on high-dimensional setting. We derive a surprisingly simple closed-form solution through rank-based covariance regularization. In particular, we propose the rank-based ℓ 1 penalization with positive definite constraints for estimating sparse covariance matrices, and the rank-based banded Cholesky decomposition regularization for estimating banded precision matrices. By taking advantage of alternating direction method of multipliers, nearest correlation matrix projection is introduced that inherits sampling properties of the unprojected one. Our work combines strengths of quantile regression and rank-based covariance regularization to simultaneously deal with nonlinearity and nonnormality for high-dimensional regression. Furthermore, the proposed method strikes a good balance between robustness and efficiency, achieves the "oracle"-like convergence rate, and provides the provable prediction interval under the high-dimensional setting. The finite-sample performance of the proposed method is also examined. The performance of our proposed rank-based method is demonstrated in a real application to analyze the protein mass spectroscopy data.

  19. Penal Code (Ordinance No. 12 of 1983), 1 July 1984.

    Science.gov (United States)

    1987-01-01

    This document contains provisions of the 1984 Penal Code of Montserrat relating to sexual offenses, abortion, offenses relating to marriage, homicide and other offenses against the person, and neglect endangering life or health. Part 8 of the Code holds that a man found guilty of raping a woman is liable to life imprisonment. Rape is deemed to involve unlawful (extramarital) sexual intercourse with a woman without her consent (this is determined if the rape involved force, threats, administration of drugs, or false representation). The Code also defines offenses in cases of incest, child abuse, prostitution, abduction, controlling the actions and finances of a prostitute, and having unlawful sexual intercourse with a mentally defective woman. Part 9 of the Code outlaws abortion unless it is conducted in an approved establishment after two medical practitioners have determined that continuing the pregnancy would risk the life or physical/mental health of the pregnant woman or if a substantial risk exists that the child would have serious abnormalities. Part 10 outlaws bigamy, and part 12 holds that infanticide performed by a mother suffering postpartum imbalances can be prosecuted as manslaughter. This part also outlaws concealment of the body of a newborn, whether that child died before, at, or after birth, and aggravated assault on any child not more than 14 years old. Part 12 makes it an offense to subject any child to neglect endangering its life or health.

  20. Justicia penal y medios de comunicación

    Directory of Open Access Journals (Sweden)

    Lic. Iván Gustavo Lello

    2001-01-01

    Full Text Available Plantearse como objeto de estudio la difusión por la prensa de procesos judiciales penales implica asumir un punto de vista multidisciplinario y multilateral. En un sistema democrático, solo en el cual es posible problematizar acerca de esta cuestión, el principio es la división de poderes y la publicidad de los actos de gobierno. En él, además, la prensa tiene una función tradicionalmente definida en la historia constitucional recogida por la tradición argentina y latinoamericana en general. Pero el espacio real de la comunicación a través de los medios de este tipo de hechos está enmarcada por tratados internacionales, la constitución y leyes positivas, e incluso con mayor minuciosidad en los códigos de procedimiento, y, en menor medida, por la deontología periodística.

  1. Diritto penale, vittimizzazione e “protagonismo” della vittima

    Directory of Open Access Journals (Sweden)

    Désirée Fondaroli

    2014-06-01

    Full Text Available The notion of a « victim » of crime is unknown in both the Italian Criminal Law and Criminal Procedure Law, with the exception of the transposed provisions of the Community acts into our national legislation and those regarding the creation of “solidarity funds” (for example, the funds to assist the victims of terrorism, of mafia, or road accidents. However, a definition is present in Article 2 of the EU Directive 2012/29/UE of the European Parliament and of the Council of 25th October 2012 establishing minimum standards on the rights, support and protection of victims of crime, and replacing the Council Framework Decision 2001/220/JHA. In place of the term “victim”, our legal system uses the traditional figure of a “person damaged as the result of crime” (Article 185 of the Penal law, who joins the proceedings as a private party to claim damages (Article 74 of the Criminal Procedure Law, the figure of the “injured party” and the associations representing the interests offended by the crime (Article 91 of the Criminal Procedure Law. The irruption of the victim into the criminal trial beyond the confines of our legal traditions produces an explosive effect. Indeed, these confines are already very large with regard to the experience of some foreign countries where often extra procedural methods of victim-offender mediation are provided.

  2. CONSECUENCIAS JURÍDICO-PENALES DEL ABSENTISMO ESCOLAR

    Directory of Open Access Journals (Sweden)

    Carlos Vázquez González

    2013-05-01

    Full Text Available El absentismo y/o el abandono escolar no son tan sólo uno de los principales problemas a los que se debe enfrentar cualquier sistema educativo, sino también un problema social relacionado con la exclusión social, la marginación y la delincuencia, ya que la investigación criminológica ha comprobado como el fracaso escolar o un temprano abandono de los estudios opera como un facilitador de la delincuencia juvenil. Cuando el absentismo o abandono escolar se produce debido a un incumplimiento injustificado por parte de los padres del deber de educar y proporcionar una formación integral a sus hijos, deber legal de asistencia inherente a la patria potestad, el Estado deberá intervenir para garantizar el derecho a la educación de los menores, recurriendo incluso al Derecho penal, mediante la aplicación del delito de abandono de familia del art. 226.1 CP.

  3. Parametric Studies of Flat Plate Trajectories Using VIC and Penalization

    Directory of Open Access Journals (Sweden)

    François Morency

    2018-01-01

    Full Text Available Flying debris is generated in several situations: when a roof is exposed to a storm, when ice accretes on rotating wind turbines, or during inflight aircraft deicing. Four dimensionless parameters play a role in the motion of flying debris. The goal of the present paper is to investigate the relative importance of four dimensionless parameters: the Reynolds number, the Froude number, the Tachikawa number, and the mass moment of inertia parameters. Flying debris trajectories are computed with a fluid-solid interaction model formulated for an incompressible 2D laminar flow. The rigid moving solid effects are modelled in the Navier-Stokes equations using penalization. A VIC scheme is used to solve the flow equations. The aerodynamic forces and moments are used to compute the acceleration and the velocity of the solid. A database of 64 trajectories is built using a two-level full factorial design for the four factors. The dispersion of the plate position at a given horizontal position decreases with the Froude number. Moreover, the Tachikawa number has a significant effect on the median plate position.

  4. Multivariable calculus with applications

    CERN Document Server

    Lax, Peter D

    2017-01-01

    This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems to partial derivatives, multiple integrals, Stokes’ and divergence theorems. Students with a background in single variable calculus are guided through a variety of problem solving techniques and practice problems. Examples from the physical sciences are utilized to highlight the essential relationship between calculus and modern science. The symbiotic relationship between science and mathematics is shown by deriving and discussing several conservation laws, and vector calculus is utilized to describe a number of physical theories via partial differential equations. Students will learn that mathematics is the language that enables scientific ideas to be precisely formulated and that science is a source for the development of mathemat...

  5. Multivariate Statistical Process Control

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2013-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...

  6. ¿ES LEGÍTIMA LA PROTECCIÓN PENAL DE LOS DERECHOS MORALES DE AUTOR?

    Directory of Open Access Journals (Sweden)

    César Alejandro Osorio Moreno

    2010-11-01

    Full Text Available En el contexto del derecho penal moderno y desde una perspectiva comparada entre el derecho penal español y el derecho penal colombiano en cuanto a la protección penal de los derechos morales de autor, se pone en discusión si es necesaria la intervención penal o no, a partir de cuestionar si en verdad se protege un bien jurídico relevante que ameritaría el mecanismo de control social más grave del que dispone el Estado que es el derecho penal, o cómo se planteará, si a partir de la protección de los derechos patrimoniales de autor se cobijan los morales tal como acontece en España en la actualidad.

  7. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  8. BN-FLEMOps pluvial - A probabilistic multi-variable loss estimation model for pluvial floods

    Science.gov (United States)

    Roezer, V.; Kreibich, H.; Schroeter, K.; Doss-Gollin, J.; Lall, U.; Merz, B.

    2017-12-01

    Pluvial flood events, such as in Copenhagen (Denmark) in 2011, Beijing (China) in 2012 or Houston (USA) in 2016, have caused severe losses to urban dwellings in recent years. These floods are caused by storm events with high rainfall rates well above the design levels of urban drainage systems, which lead to inundation of streets and buildings. A projected increase in frequency and intensity of heavy rainfall events in many areas and an ongoing urbanization may increase pluvial flood losses in the future. For an efficient risk assessment and adaptation to pluvial floods, a quantification of the flood risk is needed. Few loss models have been developed particularly for pluvial floods. These models usually use simple waterlevel- or rainfall-loss functions and come with very high uncertainties. To account for these uncertainties and improve the loss estimation, we present a probabilistic multi-variable loss estimation model for pluvial floods based on empirical data. The model was developed in a two-step process using a machine learning approach and a comprehensive database comprising 783 records of direct building and content damage of private households. The data was gathered through surveys after four different pluvial flood events in Germany between 2005 and 2014. In a first step, linear and non-linear machine learning algorithms, such as tree-based and penalized regression models were used to identify the most important loss influencing factors among a set of 55 candidate variables. These variables comprise hydrological and hydraulic aspects, early warning, precaution, building characteristics and the socio-economic status of the household. In a second step, the most important loss influencing variables were used to derive a probabilistic multi-variable pluvial flood loss estimation model based on Bayesian Networks. Two different networks were tested: a score-based network learned from the data and a network based on expert knowledge. Loss predictions are made

  9. Practical multivariate analysis

    CERN Document Server

    Afifi, Abdelmonem; Clark, Virginia A

    2011-01-01

    ""First of all, it is very easy to read. … The authors manage to introduce and (at least partially) explain even quite complex concepts, e.g. eigenvalues, in an easy and pedagogical way that I suppose is attractive to readers without deeper statistical knowledge. The text is also sprinkled with references for those who want to probe deeper into a certain topic. Secondly, I personally find the book's emphasis on practical data handling very appealing. … Thirdly, the book gives very nice coverage of regression analysis. … this is a nicely written book that gives a good overview of a large number

  10. [Extramural research funds and penal law--status of legislation].

    Science.gov (United States)

    Ulsenheimer, Klaus

    2005-04-01

    After decades of smooth functioning, the cooperation of physicians and hospitals with the industry (much desired from the side of the government in the interest of clinical research) has fallen in legal discredit due to increasingly frequent criminal inquires and proceedings for unduly privileges, corruption, and embezzlement. The discredit is so severe that the industry funding for clinical research is diverted abroad to an increasing extent. The legal elements of embezzlement assume the intentional violation of the entrusted funds against the interest of the customer. Undue privileges occur when an official requests an advantage in exchange for a service (or is promised one or takes one) in his or somebody else's interest. The elements of corruption are then given when the receiver of the undue privilege provides an illegal service or takes a discretionary decision under the influence of the gratuity. The tension between the prohibition of undue privileges (as regulated by the penal law) and the granting of extramural funds (as regulated by the administrative law in academic institutions) can be reduced through a high degree of transparency and the start of control possibilities--public announcement and authorization by the officials--as well as through exact documentation and observance of the principles of separation of interests and moderation. With the anti-corruption law of 1997, it is possible to charge of corruption also physicians employed in private institutions. In contrast, physicians in private practice are not considered in the above criminal facts. They can only be charged of misdemeanor, or called to respond to the professional board, on the basis of the law that regulates advertising for medicinal products (Heilmittelwerbegesetz).

  11. El cuerpo, el gueto y el Estado penal

    Directory of Open Access Journals (Sweden)

    Loïc Wacquant

    2010-07-01

    Full Text Available Este artículo analiza el enfoque del autor sobre la etnografía, la teoría social, y la política del conocimiento a través de un diálogo que vuelve sobre su trayectoria intelectual y los vínculos analíticos entre sus investigaciones sobre el cuerpo, la marginalidad urbana comparada y el Estado penal. Resalta las conexiones prácticas y fundamentos epistemológicos detrás de sus principales proyectos de investigación, explica las distintas maneras en que se despliega el trabajo de campo de observación en cada uno de ellos, y examina el papel de los intelectuales en las sociedades avanzadas de la era del neoliberalismo hegemónico. Rechazando tanto el empirismo de Hume como el neo-cognitivismo kantiano, el autor aboga por el uso de la etnografía como un instrumento de ruptura y construcción, la potencia del conocimiento carnal, el imperativo de la reflexividad epistémica y la necesidad de ampliar los géneros textuales y estilos con el fin de captar mejor el sabor y el dolor de la acción social. En la esfera pública, propone que las ciencias sociales pueden actuar como un disolvente de la doxa y un faro que arroja luz sobre las propiedades latentes y las tendencias desapercibidas en las transformaciones sociales a fin de generar rupturas y ampliar el debate cívico.

  12. Penalized differential pathway analysis of integrative oncogenomics studies.

    Science.gov (United States)

    van Wieringen, Wessel N; van de Wiel, Mark A

    2014-04-01

    Through integration of genomic data from multiple sources, we may obtain a more accurate and complete picture of the molecular mechanisms underlying tumorigenesis. We discuss the integration of DNA copy number and mRNA gene expression data from an observational integrative genomics study involving cancer patients. The two molecular levels involved are linked through the central dogma of molecular biology. DNA copy number aberrations abound in the cancer cell. Here we investigate how these aberrations affect gene expression levels within a pathway using observational integrative genomics data of cancer patients. In particular, we aim to identify differential edges between regulatory networks of two groups involving these molecular levels. Motivated by the rate equations, the regulatory mechanism between DNA copy number aberrations and gene expression levels within a pathway is modeled by a simultaneous-equations model, for the one- and two-group case. The latter facilitates the identification of differential interactions between the two groups. Model parameters are estimated by penalized least squares using the lasso (L1) penalty to obtain a sparse pathway topology. Simulations show that the inclusion of DNA copy number data benefits the discovery of gene-gene interactions. In addition, the simulations reveal that cis-effects tend to be over-estimated in a univariate (single gene) analysis. In the application to real data from integrative oncogenomic studies we show that inclusion of prior information on the regulatory network architecture benefits the reproducibility of all edges. Furthermore, analyses of the TP53 and TGFb signaling pathways between ER+ and ER- samples from an integrative genomics breast cancer study identify reproducible differential regulatory patterns that corroborate with existing literature.

  13. Kafka's Writing Machine: Metamorphosis in the Penal Colony

    Directory of Open Access Journals (Sweden)

    Arnold Weinstein

    1982-09-01

    Full Text Available Kafka's "In the Penal Colony" is a problematic story, largely because of the conflicting interpretations it has received: does its famous machine dispense grace or torture? Is Kafka giving us a parable of Old vs. New Law? How does the "liberal" explorer or the "liberal" reader assess the Officer's impassioned pleading for the Machine and the kind of justice it serves? A strange kind of coherence emerges, however, when one focusses on the central unifying motif of the story: understanding. The tale itself is little more than the Officer's desperate effort to make the explorer-reader understand; the machine itself makes its victim understand the nature of justice. Language is, of course, a primary vehicle for understanding, and Kafka's story dramatizes two radically opposed languages: verbal and physical. All efforts to bridge the distance between people, between matter and spirit, seem to fail, at least insofar as spoken language is concerned; the machine's mission is to create physical language, an unmediated script which is the reality of which it speaks. By writing the crime onto and into the flesh of the criminal, the machine offers a sublime and frightening figure of "visceral knowledge," of the open self as the opened self. By entering into the machine himself, the Officer undergoes the classic Kafka metamorphosis: he becomes the prisoner, and he thereby suffers knowledge. The entire parable may be seen as an illustration of the writer's yearning for a language so potent that the reader would experience, "in the flesh," the writer's words. Kafka's own narrative techniques aim at precisely such a metamorphosis in the reader.

  14. Multivariate statistical methods a primer

    CERN Document Server

    Manly, Bryan FJ

    2004-01-01

    THE MATERIAL OF MULTIVARIATE ANALYSISExamples of Multivariate DataPreview of Multivariate MethodsThe Multivariate Normal DistributionComputer ProgramsGraphical MethodsChapter SummaryReferencesMATRIX ALGEBRAThe Need for Matrix AlgebraMatrices and VectorsOperations on MatricesMatrix InversionQuadratic FormsEigenvalues and EigenvectorsVectors of Means and Covariance MatricesFurther Reading Chapter SummaryReferencesDISPLAYING MULTIVARIATE DATAThe Problem of Displaying Many Variables in Two DimensionsPlotting index VariablesThe Draftsman's PlotThe Representation of Individual Data P:ointsProfiles o

  15. pETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data.

    Science.gov (United States)

    Sun, Hokeun; Wang, Ya; Chen, Yong; Li, Yun; Wang, Shuang

    2017-06-15

    DNA methylation plays an important role in many biological processes and cancer progression. Recent studies have found that there are also differences in methylation variations in different groups other than differences in methylation means. Several methods have been developed that consider both mean and variance signals in order to improve statistical power of detecting differentially methylated loci. Moreover, as methylation levels of neighboring CpG sites are known to be strongly correlated, methods that incorporate correlations have also been developed. We previously developed a network-based penalized logistic regression for correlated methylation data, but only focusing on mean signals. We have also developed a generalized exponential tilt model that captures both mean and variance signals but only examining one CpG site at a time. In this article, we proposed a penalized Exponential Tilt Model (pETM) using network-based regularization that captures both mean and variance signals in DNA methylation data and takes into account the correlations among nearby CpG sites. By combining the strength of the two models we previously developed, we demonstrated the superior power and better performance of the pETM method through simulations and the applications to the 450K DNA methylation array data of the four breast invasive carcinoma cancer subtypes from The Cancer Genome Atlas (TCGA) project. The developed pETM method identifies many cancer-related methylation loci that were missed by our previously developed method that considers correlations among nearby methylation loci but not variance signals. The R package 'pETM' is publicly available through CRAN: http://cran.r-project.org . sw2206@columbia.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  16. Multivariate methods and forecasting with IBM SPSS statistics

    CERN Document Server

    Aljandali, Abdulkader

    2017-01-01

    This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Dis...

  17. Penalized regression techniques for prediction: a case study for predicting tree mortality using remotely sensed vegetation indices

    NARCIS (Netherlands)

    Lazaridis, D.C.; Verbesselt, J.; Robinson, A.P.

    2011-01-01

    Constructing models can be complicated when the available fitting data are highly correlated and of high dimension. However, the complications depend on whether the goal is prediction instead of estimation. We focus on predicting tree mortality (measured as the number of dead trees) from change

  18. Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

    KAUST Repository

    Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Kammoun, Abla; Al-Naffouri, Tareq Y.

    2016-01-01

    This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model

  19. Penalized linear regression for discrete ill-posed problems: A hybrid least-squares and mean-squared error approach

    KAUST Repository

    Suliman, Mohamed Abdalla Elhag

    2016-12-19

    This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrix and hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator. Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems. Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.

  20. AucPR: An AUC-based approach using penalized regression for disease prediction with high-dimensional omics data

    OpenAIRE

    Yu, Wenbao; Park, Taesung

    2014-01-01

    Motivation It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. Results We propose an AUC-based approach u...

  1. ALGUNOS APUNTES SOBRE LAS RAZONES DE LA REFORMA DEL PROCEDIMIENTO PENAL EN AMÉRICA LATINA

    Directory of Open Access Journals (Sweden)

    Pierre Gilles Bélanger

    2010-01-01

    Full Text Available Actualmente en Latinoamérica, la mayor parte de los países han modificado sus códigos penales con el objeto de tener una mejor salud procesal. En esta transición, hace falta ayuda internacional real, apoyo, colaboración e intercambio de ideas, programas, experiencias, grupos de trabajo, capacitación a nivel bilateral y multilateral dirigida por expertos para los actores en el sistema penal y para la sociedad. Todos los países de Latinoamérica, han tenido éxitos y todos tienen fallas en las reformas procesales desarrolladas en materia penal. Parece entonces oportuno, empezar el dialogo y la colaboración para contribuir a una mejor comprensión y edificación de los sistemas penales y su evolución. Para ello se requiere compartir las experiencias que han funcionado en otros países, adaptándolas al marco jurídico de cada contexto en particular. Por un lado, esto ayuda a mejorar la comprensión operacional del procedimiento penal y por otro lado, el respeto de las garantías jurídicas establecidas en las Cartas Magnas de cada país y por ende estabilidad institucional, seguridad y desarrollo económico para la sociedad.

  2. Function approximation with polynomial regression slines

    International Nuclear Information System (INIS)

    Urbanski, P.

    1996-01-01

    Principles of the polynomial regression splines as well as algorithms and programs for their computation are presented. The programs prepared using software package MATLAB are generally intended for approximation of the X-ray spectra and can be applied in the multivariate calibration of radiometric gauges. (author)

  3. Reseñas y Recensiones: Lenis, Karin. (2014). El sistema de responsabilidad penal de menores. Un estudio de las legislaciones de España y Colombia desde la teoría del Derecho Penal del Enemigo.

    OpenAIRE

    Muñetones Rozo, Ingrid Bibiana

    2015-01-01

    Reseñas y Recensiones: Reseñas y Recensiones: Lenis, Karin. (2014). El sistema de responsabilidad penal de menores. Un estudio de las legislaciones de España y Colombia desde la teoría del Derecho Penal del Enemigo. Bogotá: Grupo Editorial Ibañez, 644 p.

  4. Multivariate statistics exercises and solutions

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center  www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

  5. Teoría de la inflación penal

    OpenAIRE

    Carrasco Jiménez, Edison

    2016-01-01

    [ES]La tesis en cuestión tiene por objeto la proposición de un modelo teórico, explicativo y crítico sobre la presencia del derecho penal en la vida civil, fundado en un concepto de derecho que integre tanto lo formal como lo informal, y sobre todo, en el concepto de inflación penal. Dicha teoría se asienta sobre la hipótesis: Los aumentos o disminuciones de la legislación penal estatal y positiva se encuentran directamente relacionados(as) y dependientes a causas endógenas y exógenas. Son ca...

  6. Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

    Science.gov (United States)

    Liu, Jin; Huang, Jian; Ma, Shuangge

    2012-01-01

    Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

  7. The penalization of migrants: irregularity and prison in the construction of the neoliberal State

    Directory of Open Access Journals (Sweden)

    Ignacio González Sánchez

    2016-06-01

    Full Text Available In this paper the punitive processes affecting foreigners in Spain are analyzed. After a brief contextualization of the migratory process, and its problematization in terminology related to insecurity and crime, attention is paid to two ways of penalization: the administrative one, linked with laws for foreigners, and the penal one, reinforced by the precarious situation of these collectives. Later, an analysisi of their effects of the material —related to the labor market—, symbolic —in social categorizations— and disciplinary –in the conformation of subjectivities- is provided. The pertinence of studying processes of penalization to discern broader social dynamics and the pertince of giving more importance to these processes in studies about migrant populations is here proposed.

  8. La inimputabilidad y el tratamiento del disminuido psíquico en el proceso penal

    Directory of Open Access Journals (Sweden)

    José Manuel Rojas Salas

    2013-12-01

    Full Text Available La Constitución Política colombiana proscribe cualquier tipo de responsabilidad objetiva; en consecuencia, es necesario que la persona a la que se sancione con una pena haya actuado con culpabilidad, cosa que no sucede con los inimputables, personas que no pueden comprender la ilicitud de su conducta o determinarse de acuerdo con dicha comprensión, por lo que el Código Penal establece dos regímenes diferenciados de responsabilidad penal: uno para imputables y otro para inimputables, para quienes no se prevén penas sino medidas de seguridad. Por el contrario, la Ley 906 de 2004 no contempla un tratamiento jurídico diferenciado para quienes no tienen la capacidad de comprender o decidir voluntariamente sobre sus derechos en el proceso penal, por lo que se propone un nuevo enfoque al respecto.

  9. ¿Es el plagio una conducta reprimida por el derecho penal?

    Directory of Open Access Journals (Sweden)

    Ernesto Rengifo García

    2010-11-01

    Full Text Available ¿Será que el mensaje de la Sala Penal de la Corte Suprema es el de no activar la última ratio del sistema legal con conductas que deben ser materia de la jurisdicción civil, pero eso sí dependiendo de quién las acometa o ejecute? (se recuerda que el caso en análisis envuelve a una profesora universitaria y ¿será que la dificultad teórica y práctica de adecuación de la conducta a los tipos penales relacionados con el derecho de autor, hace que el derecho penal no sea el instrumento institucional más idóneo para reprimir la infracción a los derechos de esa particular área jurídica? La respuesta a estos interrogantes deben ser el comienzo para pensar o repensar si ese expansionismo del derecho penal que ha llegado al campo de la propiedad intelectual vale la pena revisarlo y mantenerlo. Señalaba Cesare Becaría: “Lo que impide el crimen, no es la cantidad de reprimendas penales, sino la garantía de su punición”. Si no hay certeza o garantía en el castigo, ¿valdrá la pena recurrir a la aplicación judicial de esos tipos penales?, este artículo busca abrir la discusión en este punto.

  10. ¿Es el plagio una conducta reprimida por el derecho penal?

    Directory of Open Access Journals (Sweden)

    Ernesto Rengifo García

    2010-11-01

    Full Text Available ¿Será que el mensaje de la Sala Penal de la Corte Suprema es el de no activar la ultima ratio del sistema legal con conductas que deben ser materia de la jurisdicción civil, pero eso sí dependiendo de quien las acometa o ejecute? (se recuerda que el caso en análisis envuelve a una profesora universitaria, y ¿será que la dificultad teórica y práctica de adecuación de la conducta a los tipos penales relacionados con el derecho de autor hará que el derecho penal no sea el instrumento institucional más idóneo para reprimir la infracción a los derechos de esa particular área jurídica? La respuesta a estos interrogantes deben ser el comienzo para pensar o repensar si ese expansionismo del derecho penal que ha llegado al campo de la propiedad intelectual vale la pena revisarlo y mantenerlo. Señalaba Cesare Becaría: “Lo que impide el crimen, no es la cantidad de reprimendas penales, sino la garantía de su punición”. Si no hay certeza o garantía en el castigo, ¿valdrá la pena recurrir a la aplicación judicial de esos tipos penales? Este artículo busca abrir la discusión en este punto.

  11. Penal symbolism in Serbia in the first half of the 19th century

    Directory of Open Access Journals (Sweden)

    Todorović Miljana

    2011-01-01

    Full Text Available The author explores a scarce and unusual phenomenon for the 19th century Serbia, of the emphasized nexus between crime and penalty. The author marks that special, symbolical relation of penalty, on the one hand, and sanction on the other, as 'penal symbolism'. This term refers to penalization which reflects the ties between crime and punishment by copying crime in terms of modus or place of execution, or by 'punishing' those body parts which partook in committing a crime. The author classifies the examples of preserved judgments and legislations containing penal symbolism to those referring to modus or place of execution of death penalty, those which are examples of penal symbolism related to other sanctions, and those which are examples of the symbolic talion. The author raises the questions of the origin of this phenomenon, as well as of its justification, and aims at providing answers by reconstructing legal and social framework of Serbia in the first half of the 19th century. With this objective in mind, she discusses the development of Criminal Law and its basic features, as well as the development of judiciary, the systematic institutionalization of the network of criminal courts, and, especially, the composition thereof. In the conclusion, the author rejects the possibility that penal symbolism is a product of legal transplantation or that of the continuity of Serbian medieval law. She asserts that the scarcity of material criminal law sources led to judging by 'justice and fairness', and that those facts created conditions for the primitive sense of justice to find its way into judgments and legislations as penal symbolism.

  12. El pensamiento alemán en el derecho penal argentino

    Directory of Open Access Journals (Sweden)

    Guido L. Croxatto

    2014-01-01

    Full Text Available El objetivo de este ensayo es abordar desde una perspectiva histórica la influencia del pensamiento alemán (la filosofía alemana, la dogmática alemana en el derecho penal argentino, rescatando la forma en que distintos teóricos alemanes fueron leídos y receptados en Argentina. Se pretende pensar la codificación penal argentina como un diálogo – muchas veces como una mera recepción acrítica – entre los juristas y codificadores latinoamericanos y los pensadores alemanes, en sus distintas vertientes y etapas históricas. Se analizan distintos debates –como la polémica entre el causalismo y el finalismo- tanto por la forma en que se sucedieron en Alemania, como por la forma en que se dieron en Argentina (el debate causalismo-finalismo se sucedió en los complejos años setenta en Argentina, tomando en cuenta sobretodo los contextos políticos en que surgieron esas polémicas; qué significado tuvieron estas discusiones – y qué significaba asumir determinadas posiciones – en función de los contextos políticos donde se evidenciaron. De este modo se espera trazar un panorama de la discusión actual en el derecho penal argentino, haciendo énfasis en el análisis histórico de las problemáticas que aún enfrenta el Derecho Penal, tratando de generar, al mismo tiempo, un pensamiento penal crítico, consciente – pero no rehén – de las influencias provenientes de Europa, es decir, un pensamiento penal crítico que tome en cuenta las particulares condiciones sociales e históricas de la región en que se aplica el Derecho.

  13. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  14. SkyFACT: high-dimensional modeling of gamma-ray emission with adaptive templates and penalized likelihoods

    Energy Technology Data Exchange (ETDEWEB)

    Storm, Emma; Weniger, Christoph [GRAPPA, Institute of Physics, University of Amsterdam, Science Park 904, 1090 GL Amsterdam (Netherlands); Calore, Francesca, E-mail: e.m.storm@uva.nl, E-mail: c.weniger@uva.nl, E-mail: francesca.calore@lapth.cnrs.fr [LAPTh, CNRS, 9 Chemin de Bellevue, BP-110, Annecy-le-Vieux, 74941, Annecy Cedex (France)

    2017-08-01

    We present SkyFACT (Sky Factorization with Adaptive Constrained Templates), a new approach for studying, modeling and decomposing diffuse gamma-ray emission. Like most previous analyses, the approach relies on predictions from cosmic-ray propagation codes like GALPROP and DRAGON. However, in contrast to previous approaches, we account for the fact that models are not perfect and allow for a very large number (∼> 10{sup 5}) of nuisance parameters to parameterize these imperfections. We combine methods of image reconstruction and adaptive spatio-spectral template regression in one coherent hybrid approach. To this end, we use penalized Poisson likelihood regression, with regularization functions that are motivated by the maximum entropy method. We introduce methods to efficiently handle the high dimensionality of the convex optimization problem as well as the associated semi-sparse covariance matrix, using the L-BFGS-B algorithm and Cholesky factorization. We test the method both on synthetic data as well as on gamma-ray emission from the inner Galaxy, |ℓ|<90{sup o} and | b |<20{sup o}, as observed by the Fermi Large Area Telescope. We finally define a simple reference model that removes most of the residual emission from the inner Galaxy, based on conventional diffuse emission components as well as components for the Fermi bubbles, the Fermi Galactic center excess, and extended sources along the Galactic disk. Variants of this reference model can serve as basis for future studies of diffuse emission in and outside the Galactic disk.

  15. Maritime environmental penal law. International and German legislation; Maritimes Umweltstrafrecht. Voelkerrechtliche Grundlagen und deutsches Recht

    Energy Technology Data Exchange (ETDEWEB)

    Eller, Jan Frederik

    2017-07-01

    The book on maritime environmental penal law discusses the following issues: part I: introduction into the importance of oceanic environment and its thread, requirement of protective measures,; part II: focus of the study and terminology: oceanic pollution, maritime environmental legislation, international legislation; part 3: international legislative regulations concerning the protection of maritime environment: avoidance of environmental pollution, maritime legislative agreements, existing protective institutions; part 4: state penal power concerning maritime environmental protection; part 5: statutory offense according to German legislation; perspectives for regulations concerning criminal acts on sea.

  16. La eficacia de la Prueba Indiciaria en el Proceso Penal Ecuatoriano

    OpenAIRE

    Pérez Medina, Lenin

    2007-01-01

    La eficacia de la prueba Indiciaria en el Proceso Penal Ecuatoriano, a tomado una nueva dimensión en nuestro sistema procesal, ya que a partir de la vigencia del nuevo Código de Procedimiento Penal, se ha orientado a garantizar la aplicación del debido proceso, en todos los parámetros que la constitución establece, en el presente trabajo estudiamos diferentes tópicos como presunción , sospecha , conjetura, vestigio, huella y rastro donde podría aparecer la prueba indiciaria, si...

  17. Feminicidio y derecho penal: herramientas para su mejor aplicación

    Directory of Open Access Journals (Sweden)

    Jhoanna Caterine Prieto Moreno

    2012-01-01

    Full Text Available El numeral 11 del artículo 104 del Código Penal colombiano introdujo como causal de agravación del homicidio aquella acción que se comete contra una mujer en razón a su condición de género, pero que ello no llega a ser suficiente en razón al desconocimiento que se tiene por parte del aparato jurisdiccional penal para su debida aplicación, en razón a que no se tiene claridad sobre las motivaciones que llevaron al victimario a cometer dicho homicidio (feminicidio.

  18. El garantismo y el punitivismo en el Código Orgánico Integral Penal

    OpenAIRE

    Sebastián Cornejo Aguiar

    2016-01-01

    El objetivo del presente artículo es determinar la necesidad de la existencia de una parte punitivista y una garantista dentro del Código Orgánico Integral Penal, partiendo del estudio de la actualización doctrinaria en materia penal dentro del ordenamiento jurídico ecuatoriano, considerando que al ser el Ecuador un Estado constitucional de derechos y justicia, nos inspira a la construcción de mecanismos que tengan como fundamento y fin la tutela de las libertades del individuo, frente a las ...

  19. AS TRÊS DIMENSÕES DA PROPORCIONALIDADE NO DIREITO PENAL

    OpenAIRE

    Sebástian Borges de Albuquerque Mello

    2015-01-01

    O presente artigo analisa as manifestações do princípio da proporcionalidade, relacionando-o com diversos princípios fundamentais do Direito Penal. Assim, relaciona-se necessidade com intervenção mínima, adequação com adequação social e a proporcionalidade em sentido estrito com a compatibilização harmônica e axiológica das penas dentro do sistema jurídico-penal.

  20. El Ministerio Público y la “Atención Primaria” de la Conflictividad Penal

    OpenAIRE

    Mendaña, Ricardo J.; Arias Salgado, Alicia

    2008-01-01

    El artículo revisa la aplicación práctica de los conceptos pertinentes a la mejora de la justicia penal. La adopción de nuevos paradigmas y líneas de acción para intervenir frente a los conflictos penales implica situar la mejora de la atención primaria como una estrategia de intervención superior a las actividades de modelos tradicionales de respuesta judicial. This article looks at the practical application of relevant concepts when improving crime justice. The adoption of new paradigms ...

  1. El pensamiento alemán en el derecho penal argentino

    OpenAIRE

    Guido L. Croxatto; Eugenio R. Zaffaroni

    2014-01-01

    El objetivo de este ensayo es abordar desde una perspectiva histórica la influencia del pensamiento alemán (la filosofía alemana, la dogmática alemana) en el derecho penal argentino, rescatando la forma en que distintos teóricos alemanes fueron leídos y receptados en Argentina. Se pretende pensar la codificación penal argentina como un diálogo – muchas veces como una mera recepción acrítica – entre los juristas y codificadores latinoamericanos y los pensado...

  2. El nuevo tratamiento penal del blanqueo de capitales en el derecho brasileño (ley 12.683/2012)

    OpenAIRE

    Regis Prado, Luiz

    2013-01-01

    Análisis de los impactos causados por la nueva ley (12.683/2012) sobre el tratamiento penal del blanqueo de capitales This is an analysis of the impacts caused by the law 12.683/2012 concerning the penal treatment of money laudering

  3. Environmental protection and penal law in Greece - a comparison with the German penal code on environmental matters. Der strafrechtliche Umweltschutz in Griechenland unter besonderer Beruecksichtigung des Deutschen Umweltstrafrechts

    Energy Technology Data Exchange (ETDEWEB)

    Karamanidis, G.

    1985-01-01

    The first chapter outlines the ecological situation of Greece, while the second chapter presents the legal foundations of environmental protection in Greece. Secondary laws are mentioned, as these are generally the laws in which penal liabilities are stated. The present environmental protection regulations are found to be unsatisfactory and unfit for preventing environmental damage. A new legislative structure is proposed on the basis of German environmental protection standards. (orig./HSCH).

  4. Processing data collected from radiometric experiments by multivariate technique

    International Nuclear Information System (INIS)

    Urbanski, P.; Kowalska, E.; Machaj, B.; Jakowiuk, A.

    2005-01-01

    Multivariate techniques applied for processing data collected from radiometric experiments can provide more efficient extraction of the information contained in the spectra. Several techniques are considered: (i) multivariate calibration using Partial Least Square Regression and Artificial Neural Network, (ii) standardization of the spectra, (iii) smoothing of collected spectra were autocorrelation function and bootstrap were used for the assessment of the processed data, (iv) image processing using Principal Component Analysis. Application of these techniques is illustrated on examples of some industrial applications. (author)

  5. Política de despenalización como medio eficaz para una justicia penal justa

    Directory of Open Access Journals (Sweden)

    Rogelio Barba Álvarez

    2008-01-01

    Full Text Available El actual sistema de justicia penal en México se encuentra en una grave crisis, derivada de la falta de una adecuada política criminal y técnica legislativa. La política de despenalización serviría para resolver muchos de los problemas que se originan por la pésima justicia penal que actualmente impera en México. Por este medio se podría resolver el problema de la hipertrofia legislativa, la antinomia de tipos penales, el fortalecimiento de un subsistema sancionatorio más benévolo que aquel basado en la amenaza penal, y sobre todo de la unificación de la legislación penal en nuestro país, para lograr la anhelada justicia justa.

  6. MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

    Science.gov (United States)

    Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

  7. Distributed Monitoring of the R2 Statistic for Linear Regression

    Data.gov (United States)

    National Aeronautics and Space Administration — The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and...

  8. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  9. Multivariate analysis: models and method

    International Nuclear Information System (INIS)

    Sanz Perucha, J.

    1990-01-01

    Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

  10. Model Checking Multivariate State Rewards

    DEFF Research Database (Denmark)

    Nielsen, Bo Friis; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    We consider continuous stochastic logics with state rewards that are interpreted over continuous time Markov chains. We show how results from multivariate phase type distributions can be used to obtain higher-order moments for multivariate state rewards (including covariance). We also generalise...

  11. Multivariate analysis methods in physics

    International Nuclear Information System (INIS)

    Wolter, M.

    2007-01-01

    A review of multivariate methods based on statistical training is given. Several multivariate methods useful in high-energy physics analysis are discussed. Selected examples from current research in particle physics are discussed, both from the on-line trigger selection and from the off-line analysis. Also statistical training methods are presented and some new application are suggested [ru

  12. Multivariate covariance generalized linear models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Jørgensen, Bent

    2016-01-01

    are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...

  13. Simulation of impulsively started flow past a sphere and a disc using iterative brinkman penalization

    DEFF Research Database (Denmark)

    Spietz, Henrik Juul; Hejlesen, Mads Mølholm; Walther, Jens Honore

    We present an iterative Brinkman penalization scheme to enforce the no-slip condition onsolid boundaries in three-dimensional ow simulations. We use a high-order particle-meshvortex method, where the velocity field is obtained from the vorticity field by solving a Poisson equation on a Cartesian...

  14. 49 CFR 26.47 - Can recipients be penalized for failing to meet overall goals?

    Science.gov (United States)

    2010-10-01

    ... Goals, Good Faith Efforts, and Counting § 26.47 Can recipients be penalized for failing to meet overall... administer your program in good faith. (b) If you do not have an approved DBE program or overall goal, or if you fail to implement your program in good faith, you are in noncompliance with this part. ...

  15. Variational and penalization methods for studying connecting orbits of Hamiltonian systems

    Directory of Open Access Journals (Sweden)

    Chao-Nien Chen

    2000-08-01

    Full Text Available In this article, we consider a class of second order Hamiltonian systems that possess infinite or finite number of equilibria. Variational arguments will be used to study the existence of connecting orbits joining pairs of equilibria. Applying penalization methods, we obtain various patterns for multibump homoclinics and heteroclinics of Hamiltonian systems.

  16. The Role of the Environmental Health Specialist in the Penal and Correctional System

    Science.gov (United States)

    Walker, Bailus, Jr.; Gordon, Theodore J.

    1976-01-01

    Implementing a health and hygiene program in penal systems necessitates coordinating the entire staff. Health specialists could participate in facility planning and management, policy formation, and evaluation of medical care, housekeeping, and food services. They could also serve as liaisons between correctional staff and governmental or…

  17. On the use of a penalized least squares method to process kinematic full-field measurements

    International Nuclear Information System (INIS)

    Moulart, Raphaël; Rotinat, René

    2014-01-01

    This work is aimed at exploring the performances of an alternative procedure to smooth and differentiate full-field displacement measurements. After recalling the strategies currently used by the experimental mechanics community, a short overview of the available smoothing algorithms is drawn up and the requirements that such an algorithm has to fulfil to be applicable to process kinematic measurements are listed. A comparative study of the chosen algorithm is performed including the 2D penalized least squares method and two other commonly implemented strategies. The results obtained by penalized least squares are comparable in terms of quality to those produced by the two other algorithms, while the penalized least squares method appears to be the fastest and the most flexible. Unlike both the other considered methods, it is possible with penalized least squares to automatically choose the parameter governing the amount of smoothing to apply. Unfortunately, it appears that this automation is not suitable for the proposed application since it does not lead to optimal strain maps. Finally, it is possible with this technique to perform the derivation to obtain strain maps before smoothing them (while the smoothing is normally applied to displacement maps before the differentiation), which can lead in some cases to a more effective reconstruction of the strain fields. (paper)

  18. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  19. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  20. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  1. A primer of multivariate statistics

    CERN Document Server

    Harris, Richard J

    2014-01-01

    Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why

  2. Non-Asymptotic Oracle Inequalities for the High-Dimensional Cox Regression via Lasso.

    Science.gov (United States)

    Kong, Shengchun; Nan, Bin

    2014-01-01

    We consider finite sample properties of the regularized high-dimensional Cox regression via lasso. Existing literature focuses on linear models or generalized linear models with Lipschitz loss functions, where the empirical risk functions are the summations of independent and identically distributed (iid) losses. The summands in the negative log partial likelihood function for censored survival data, however, are neither iid nor Lipschitz.We first approximate the negative log partial likelihood function by a sum of iid non-Lipschitz terms, then derive the non-asymptotic oracle inequalities for the lasso penalized Cox regression using pointwise arguments to tackle the difficulties caused by lacking iid Lipschitz losses.

  3. Proceso penal, privacidad y autodeterminación informativa en la persecución penal de la delincuencia organizada. Un análisis desde la perspectiva del derecho procesal penal alemán

    Directory of Open Access Journals (Sweden)

    Angélica Romero Sánchez

    2015-08-01

    Full Text Available El surgimiento y fortalecimiento de la delincuencia organizada en las últimas décadas del siglo XX determinan un cambio en las herramientas de investigación penal y su regulación en muchos sistemas jurídicos. Estos instrumentos, apoyados en el desarrollo de nuevas tecnologías, poseen características que los diferencian de las clásicas medidas de investigación. En el presente artículo se describe esta transformación en el proceso penal alemán (I, analizando el contexto en que se ha originado la regulación de estos nuevos instrumentos de investigación penal de la delincuencia organizada (A, estudiando sus características especiales (B y deduciendo las características generales (C. Posteriormente se reseña, desde la perspectiva de la doctrina y jurisprudencia alemanas, el significado de dos libertades fundamentales afectadas con la ejecución de tales mecanismos (II: el derecho a la privacidad (A y el derecho a la autodeterminación informativa (B. Cómo conciliar el uso de estas medidas de investigación y su afectación a las garantías fundamentales mencionadas, constituye el tercer apartado del artículo (III. En este se examinan los diferentes presupuestos desarrollados por la doctrina y la jurisprudencia alemanas, para legitimar este tipo de intervenciones. Seguidamente (IV se describe, de manera general, la estructura desarrollada por el legislador alemán para la regulación de las medidas de investigación aquí tratadas, teniendo en cuenta los presupuestos señalados en el acápite precedente. Finalmente, las conclusiones están dirigidas a reflexionar acerca de la importancia de una regulación estructurada de aquellas medidas de investigación, de carácter secreto y utilizadas en la persecución penal de determinados tipos de criminalidad, como la delincuencia organizada, cuyo empleo acarrea graves injerencias en derechos fundamentales.

  4. El cuerpo, el gueto y el Estado penal

    Directory of Open Access Journals (Sweden)

    Loïc Wacquant

    2010-02-01

    ="background: white none repeat scroll 0% 0%; -moz-background-clip: border; -moz-background-origin: padding; -moz-background-inline-policy: continuous">
    política del conocimiento a través de un diálogo que vuelve sobre su trayectoria intelectual y los vínculos analíticos entre sus investigaciones sobre el cuerpo, la marginalidad urbana comparada y el Estado penal. Resalta las conexiones prácticas y fundamentos epistemológicos detrás de sus principales proyectos de investigación, explica las distintas maneras en que se despliega el trabajo de campo de observación en cada uno de ellos, y examina el papel de los intelectuales en las sociedades avanzadas
    de la era del neoliberalismo hegemónico. Rechazando tanto el empirismo de Hume como el neo-cognitivismo kantiano, el autor aboga por el uso de la etnografía como un instrumento de ruptura y construcción, la potencia del conocimiento carnal, el imperativo de la reflexividad epistémica y la necesidad de ampliar los géneros textuales y estilos con el fin de captar mejor el sabor y el dolor de la acción social. En la esfera pública, propone que las ciencias sociales pueden actuar como un disolvente de la doxa y un faro que arroja luz sobre las propiedades latentes y las tendencias desapercibidas en
    las transformaciones sociales a fin de generar rupturas y ampliar el debate cívico.La protección penal a niños y adolescentes víctimas de violencia familiar

    OpenAIRE

    Salazar Mariño, Carlos Rosendo

    2014-01-01

    La presente investigación titulada "La Protección Penal a Niños y Adolescentes Víctimas de Violencia Familiar" describe los problemas que presentan el sistema de administración de justicia penal respecto a la protección de los derechos de los niños, niñas y adolescentes que sufren violencia en el hogar. Tiene como objetivo principal analizar y describir la protección penal de Jos derechos de los niños, niñas y adolescentes víctimas de violencia familiar, conocer cómo se aplica los principios ...

  5. A TUTELA PENAL DO MEIO AMBIENTE E SUA (INCOMPATIBILIDADE COM A INTERVENÇÃO MÍNIMA

    Directory of Open Access Journals (Sweden)

    Jamille Clara Alves Adamczyk

    2017-06-01

    Full Text Available Considerando que o Direito Penal deve atuar como última via e para tutelar os bens jurídicos mais relevantes, propõe-se a analisar se a imputação da responsabilidade penal ambiental iria de encontro com a premissa da intervenção mínima. Assim, tem-se como objetivo do presente estudo analisar se a responsabilização penal no âmbito do direito ambiental viola o princípio da intervenção mínima.

  6. On directional multiple-output quantile regression

    Czech Academy of Sciences Publication Activity Database

    Paindaveine, D.; Šiman, Miroslav

    2011-01-01

    Roč. 102, č. 2 (2011), s. 193-212 ISSN 0047-259X R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:Commision EC(BE) Fonds National de la Recherche Scientifique Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate quantile * quantile regression * multiple-output regression * halfspace depth * portfolio optimization * value-at risk Subject RIV: BA - General Mathematics Impact factor: 0.879, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/siman-0364128.pdf

  7. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  8. Directional quantile regression in Octave (and MATLAB)

    Czech Academy of Sciences Publication Activity Database

    Boček, Pavel; Šiman, Miroslav

    2016-01-01

    Roč. 52, č. 1 (2016), s. 28-51 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * multivariate quantile * depth contour * Matlab Subject RIV: IN - Informatics, Computer Science Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/bocek-0458380.pdf

  9. Multivariate Statistical Process Control Charts: An Overview

    OpenAIRE

    Bersimis, Sotiris; Psarakis, Stelios; Panaretos, John

    2006-01-01

    In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as p...

  10. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  11. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  12. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  13. application of multilinear regression analysis in modeling of soil

    African Journals Online (AJOL)

    Windows User

    Accordingly [1, 3] in their work, they applied linear regression ... (MLRA) is a statistical technique that uses several explanatory ... order to check this, they adopted bivariate correlation analysis .... groups, namely A-1 through A-7, based on their relative expected ..... Multivariate Regression in Gorgan Province North of Iran” ...

  14. Multivariate Generalized Multiscale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Anne Humeau-Heurtier

    2016-11-01

    Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.

  15. Will hypertension performance measures used for pay-for-performance programs penalize those who care for medically complex patients?

    Science.gov (United States)

    Petersen, Laura A; Woodard, Lechauncy D; Henderson, Louise M; Urech, Tracy H; Pietz, Kenneth

    2009-06-16

    There is concern that performance measures, patient ratings of their care, and pay-for-performance programs may penalize healthcare providers of patients with multiple chronic coexisting conditions. We examined the impact of coexisting conditions on the quality of care for hypertension and patient perception of overall quality of their health care. We classified 141 609 veterans with hypertension into 4 condition groups: those with hypertension-concordant (diabetes mellitus, ischemic heart disease, dyslipidemia) and/or -discordant (arthritis, depression, chronic obstructive pulmonary disease) conditions or neither. We measured blood pressure control at the index visit, overall good quality of care for hypertension, including a follow-up interval, and patient ratings of satisfaction with their care. Associations between condition type and number of coexisting conditions on receipt of overall good quality of care were assessed with logistic regression. The relationship between patient assessment and objective measures of quality was assessed. Of the cohort, 49.5% had concordant-only comorbidities, 8.7% had discordant-only comorbidities, 25.9% had both, and 16.0% had none. Odds of receiving overall good quality after adjustment for age were higher for those with concordant comorbidities (odds ratio, 1.78; 95% confidence interval, 1.70 to 1.87), discordant comorbidities (odds ratio, 1.32; 95% confidence interval, 1.23 to 1.41), or both (odds ratio, 2.25; 95% confidence interval, 2.13 to 2.38) compared with neither. Findings did not change after adjustment for illness severity and/or number of primary care and specialty care visits. Patient assessment of quality did not vary by the presence of coexisting conditions and was not related to objective ratings of quality of care. Contrary to expectations, patients with greater complexity had higher odds of receiving high-quality care for hypertension. Subjective ratings of care did not vary with the presence or absence of

  16. On the Optimality of Multivariate S-Estimators

    NARCIS (Netherlands)

    Croux, C.; Dehon, C.; Yadine, A.

    2010-01-01

    In this paper we maximize the efficiency of a multivariate S-estimator under a constraint on the breakdown point. In the linear regression model, it is known that the highest possible efficiency of a maximum breakdown S-estimator is bounded above by 33% for Gaussian errors. We prove the surprising

  17. LA RESPONSABILIDAD PENAL DEL NOTARIO EN COLOMBIA EN EL EJERCICIO DE SUS FUNCIONES PÚBLICAS. ESTUDIO DESDE LA PERSPECTIVA DEL DERECHO PENAL ECONÓMICO

    Directory of Open Access Journals (Sweden)

    Jorge Arturo Abello Gual

    2015-01-01

    Full Text Available Este artículo trata el tema de los delitos aplicables a la actividad notarial y del estudio de las figuras especiales de la teoría del delito, que le serían aplicables a la función notarial. En este orden de ideas, queda planteada la discusión en torno a la responsabilidad penal del notario y de sus empleados, en el ejercicio de su función pública.

  18. Understanding poisson regression.

    Science.gov (United States)

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  19. EXPLORATORY DATA ANALYSIS AND MULTIVARIATE STRATEGIES FOR REVEALING MULTIVARIATE STRUCTURES IN CLIMATE DATA

    Directory of Open Access Journals (Sweden)

    2016-12-01

    Full Text Available This paper is on data analysis strategy in a complex, multidimensional, and dynamic domain. The focus is on the use of data mining techniques to explore the importance of multivariate structures; using climate variables which influences climate change. Techniques involved in data mining exercise vary according to the data structures. The multivariate analysis strategy considered here involved choosing an appropriate tool to analyze a process. Factor analysis is introduced into data mining technique in order to reveal the influencing impacts of factors involved as well as solving for multicolinearity effect among the variables. The temporal nature and multidimensionality of the target variables is revealed in the model using multidimensional regression estimates. The strategy of integrating the method of several statistical techniques, using climate variables in Nigeria was employed. R2 of 0.518 was obtained from the ordinary least square regression analysis carried out and the test was not significant at 5% level of significance. However, factor analysis regression strategy gave a good fit with R2 of 0.811 and the test was significant at 5% level of significance. Based on this study, model building should go beyond the usual confirmatory data analysis (CDA, rather it should be complemented with exploratory data analysis (EDA in order to achieve a desired result.

  1. Two-step variable selection in quantile regression models

    Directory of Open Access Journals (Sweden)

    FAN Yali

    2015-06-01

    Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

  2. Multivariate stochastic simulation with subjective multivariate normal distributions

    Science.gov (United States)

    P. J. Ince; J. Buongiorno

    1991-01-01

    In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal...

  3. Burocracias penales, administración institucional de conflictos y ciudadanía: Experiencia comparada entre Brasil y Argentina

    OpenAIRE

    Marta Fernández Patallo

    2010-01-01

    TISCORNIA Sofía, KANT DE LIMA Roberto y EILBAUM, Lucía (comp.). 2009. Burocracias penales, administración institucional de conflictos y ciudadanía. Experiencia comparada entre Brasil y Argentina. Buenos Aires: Antropofagia.

  4. Analysis gives the penal treatment in Cuba to the tied infractions to the use and conservation gives radioactive substances

    International Nuclear Information System (INIS)

    Perez Gonzalez, F.; Perez Velazquez, R.S.; Fornet, R.O.; Reyes Fajardo, E.

    1998-01-01

    The work refers the realized analysis to the Law 62 the Cuban penal code that with establishing to the treatment of the infractions referred standard's to the uses and conservation the radioactive substances and other ionizing radiations sources

  5. Multivariate Matrix-Exponential Distributions

    DEFF Research Database (Denmark)

    Bladt, Mogens; Nielsen, Bo Friis

    2010-01-01

    be written as linear combinations of the elements in the exponential of a matrix. For this reason we shall refer to multivariate distributions with rational Laplace transform as multivariate matrix-exponential distributions (MVME). The marginal distributions of an MVME are univariate matrix......-exponential distributions. We prove a characterization that states that a distribution is an MVME distribution if and only if all non-negative, non-null linear combinations of the coordinates have a univariate matrix-exponential distribution. This theorem is analog to a well-known characterization theorem...

  6. Local bilinear multiple-output quantile/depth regression

    Czech Academy of Sciences Publication Activity Database

    Hallin, M.; Lu, Z.; Paindaveine, D.; Šiman, Miroslav

    2015-01-01

    Roč. 21, č. 3 (2015), s. 1435-1466 ISSN 1350-7265 R&D Projects: GA MŠk(CZ) 1M06047 Institutional support: RVO:67985556 Keywords : conditional depth * growth chart * halfspace depth * local bilinear regression * multivariate quantile * quantile regression * regression depth Subject RIV: BA - General Mathematics Impact factor: 1.372, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/siman-0446857.pdf

  7. Mixture of Regression Models with Single-Index

    OpenAIRE

    Xiang, Sijia; Yao, Weixin

    2016-01-01

    In this article, we propose a class of semiparametric mixture regression models with single-index. We argue that many recently proposed semiparametric/nonparametric mixture regression models can be considered special cases of the proposed model. However, unlike existing semiparametric mixture regression models, the new pro- posed model can easily incorporate multivariate predictors into the nonparametric components. Backfitting estimates and the corresponding algorithms have been proposed for...

  8. A pseudo-penalized quasi-likelihood approach to the spatial misalignment problem with non-normal data.

    Science.gov (United States)

    Lopiano, Kenneth K; Young, Linda J; Gotway, Carol A

    2014-09-01

    Spatially referenced datasets arising from multiple sources are routinely combined to assess relationships among various outcomes and covariates. The geographical units associated with the data, such as the geographical coordinates or areal-level administrative units, are often spatially misaligned, that is, observed at different locations or aggregated over different geographical units. As a result, the covariate is often predicted at the locations where the response is observed. The method used to align disparate datasets must be accounted for when subsequently modeling the aligned data. Here we consider the case where kriging is used to align datasets in point-to-point and point-to-areal misalignment problems when the response variable is non-normally distributed. If the relationship is modeled using generalized linear models, the additional uncertainty induced from using the kriging mean as a covariate introduces a Berkson error structure. In this article, we develop a pseudo-penalized quasi-likelihood algorithm to account for the additional uncertainty when estimating regression parameters and associated measures of uncertainty. The method is applied to a point-to-point example assessing the relationship between low-birth weights and PM2.5 levels after the onset of the largest wildfire in Florida history, the Bugaboo scrub fire. A point-to-areal misalignment problem is presented where the relationship between asthma events in Florida's counties and PM2.5 levels after the onset of the fire is assessed. Finally, the method is evaluated using a simulation study. Our results indicate the method performs well in terms of coverage for 95% confidence intervals and naive methods that ignore the additional uncertainty tend to underestimate the variability associated with parameter estimates. The underestimation is most profound in Poisson regression models. © 2014, The International Biometric Society.

  9. La impronta genética de Ihering en la dogmática penal

    Directory of Open Access Journals (Sweden)

    Carlos Arturo Gómez Pavajeau

    2010-06-01

    Full Text Available Se ocupa el presente estudio de dar cuenta de la importancia de Rudolf Von Ihering para el Derecho penal y sus desarrollos dogmáticos. La impronta de su importancia marcó el descubrimiento de un concepto de antijuridicidad independiente de la culpabilidad, inauguró la discusión entre objetivistas y subjetivistas en materia del injusto y visionó un concepto final de acción fundado teleológicamente; lo cual significa que su pensamiento y el núcleo duro de la discusión permanece con plena actualidad, especialmente para el entendimiento de un Derecho Penal Liberal ante las arremetidas de nuevas concepciones que, eludiendo el tema de los cuestionamientos al subjetivismo, legitiman instituciones que son paradigmáticas a dicho pensamiento.

  10. La impronta genética de Ihering en la dogmática penal

    Directory of Open Access Journals (Sweden)

    Carlos Arturo Gómez Pavajeau

    2010-07-01

    Full Text Available Se ocupa el presente estudio de dar cuenta de la importancia de Rudolf Von Ihering para el Derecho penal y sus desarrollos dogmáticos. La impronta de su importancia marcó el descubrimiento de un concepto de antijuridicidad independiente de la culpabilidad, inauguró la discusión entre objetivistas y subjetivistas en materia del injusto y visionó un concepto final de acción fundado teleológicamente; lo cual significa que su pensamiento y el núcleo duro de la discusión permanece con plena actualidad, especialmente para el entendimiento de un Derecho Penal Liberal ante las arremetidas de nuevas concepciones que, eludiendo el tema de los cuestionamientos al subjetivismo, legitiman instituciones que son paradigmáticas a dicho pensamiento.

  11. LA CONCILIACIÓN PREPROCESAL EN EL SISTEMA PENAL ACUSATORIO Y SUS PRINCIPALES APORTES

    Directory of Open Access Journals (Sweden)

    Dayana Becerra

    2009-01-01

    Full Text Available La aproximación que se efectúa en el presente estudio, inicia con un acercamiento al concepto de conciliación como mecanismo alternativo de resolución de conflictos, estableciendo los rasgos generales de esta figura; para posteriormente analizar el antecedente inmediato de la conciliación preprocesal en la ley 600 de 2.000, que abrió camino para concederle en materia penal a este mecanismo mayor importancia. Subsiguientemente se profundiza en la conciliación preprocesal consagrada expresamente en la ley 906 de 2004, y se analizan los cambios generados, para así conocer sus características, y determinar sus principales aportes, en el marco del sistema penal acusatorio.

  12. Building and toning: An analysis of the institutionalization of mediation in penal matters in Hungary

    Directory of Open Access Journals (Sweden)

    Fellegi Borbála

    2011-01-01

    Full Text Available Since 1 January 2007, victims of crimes and offenders have been offered the chance to have recourse to mediation in Hungary. This paper will first give a short overview of the current situation of mediation in penal matters in Hungary, then it will discuss some general phenomena and dilemmas concerning the general introduction of mediation. After that, I will present a SWOT analysis1 of the current Hungarian mediation system in penal matters. The main goal of this article is to set up certain criteria for the further development of the restorative approach. The lessons we have learnt, the strengths and opportunities of the system and the identification of weaknesses might prove useful for other countries when they choose to introduce mediation, and in relation to the protection of victims in particular.

  13. Fundamentos de la detención preventiva en el procedimiento penal colombiano

    Directory of Open Access Journals (Sweden)

    Leonardo Cruz Bolívar

    2012-12-01

    Full Text Available La contribución se ocupa de analizar en concreto los principios que rigen la privación preventiva de la libertad en el procedimiento penal, desde el punto de vista constitucional, legal y de instrumentos internacionales, buscando armonizar los criterios que utilizan los jueces de garantías al momento de resolver la solicitud del fiscal en esta materia. El principio de proporcionalidad constitucional, los elementos desarrollados legalmente y los pronunciamientos del sistema interamericano de derechos humanos dan base a las interpretaciones que se proponen en el artículo, buscando proteger la libertad, sin renunciar a las necesidades básicas de la justicia y la sociedad que requieren un proceso penal eficiente y que responda a la realidad nacional.

  14. Construção e identidade da dogmática penal: do garantismo prometido ao garantimo prisioneiro

    Directory of Open Access Journals (Sweden)

    Vera Regina Pereira de Andrade

    2008-09-01

    Full Text Available Tratamos, neste artigo, da construção eidentidade da Dogmática Penal enquanto paradigmade Ciência Penal dominante na modernidade. E ofazemos através de três passos, a saber: demarcandosuas matrizes e modelos fundacionais (num primeiromomento em nível do saber e, num segundomomento, em nível da relação saber-poder; demarcandoo que é a Dogmática Penal desde suaauto-imagem (desde uma escuta à voz dospenalistas que protagonizam e compartilham seuparadigma para, ao final, problematizá-la em nívelfuncional, apontando a contradição entre suasfunções declaradas (garantismo prometido e asfunções realmente cumpridas na modernidade(garantismo prisioneiro. A Dogmática aparece,nesta perspectiva, como um protagonismo decisivono processo de instrumentalização e legitimaçãodo controle penal moderno e da ordem social queele co-constitui.Abstract: This article deals with the constructionand identity of the Penal Dogmatic, as a paradigmof the Penal Science, dominant in modernity. Thisis done in three steps: delineating their originsand foundational models (at a first moment at thelevel of knowledge and, in a second, in aknowledge power moment determining what isPenal Dogmatic, since its self image (since alistening to a voice of penalists whom have carriedout and shared their paradigm, to, at the end,transform it into a problem at a functional level,pointing out the contradictions between thedeclared functions (promise guarantism and thereal functions promised in modernity (prisonguarantism. The Dogmatic appears, in thisperspective, as a decisive carry out in the processof instrumentalizating and legitimating of themodern penal control, and of the social order,which it constructed.

  15. MEMBANGUN POLITIK KRIMINAL PADA PERTAMBANGAN BATUBARA YANG MENYEJAHTERAKAN MASYARAKAT MELALUI SARANA NON-PENAL

    Directory of Open Access Journals (Sweden)

    Arif Firmansyah

    2016-04-01

    Full Text Available In Article 33 paragraph (3 of the Constitution of 1945, states earth water and natural resources contained therein controlled by the state and used for the welfare of the people. The realization of such mastery by delegating the authority to manage the natural resources of the state to the company is to provide state Mining Permit or Special Mining Permit. In protecting and overseeing the company that is engaged in coal mining government passed Law Number 4 of 2009 on Mineral and Coal Mining. In Article 162 of Law Number 4 of 2009 states that every person who impede or interfere mining activities from business license holders of mining and business permit of the mining specifically penalized by fines or imprisonment. The article shows a process of criminalization an action (criminal policy, which aim to protect the companies that already have a Mining Permit, but the criminal policy is contrary to the purpose of the criminal policy is an effort for the welfare of society and policies the protection of society, the existence of Article 162 of Law Minerals coal and coal mining communities can impede convicted. In the case of the counteraction form caused they want to protect the environment or their ancestral lands from exploration activities. So it is activity is not uncommon form of criminal policy by means of criminal law that gives rise to new conflicts. Therefore the criminal policy should be shifted from penal facilities to non-penal policy more accommodating community participation, so that the purpose of the criminal policy, namely the welfare of society and protect the community can be realized.Keywords: Political Criminal, Mining, Non-Penal

  16. LA IMPUGNACIÓN DE LA CREDIBILIDAD DE TESTIGOS EN EL SISTEMA PENAL ACUSATORIO

    Directory of Open Access Journals (Sweden)

    Alejandro Decastro González

    2008-05-01

    Full Text Available Este trabajo explica en qué consiste el procedimiento de impugnación de la credibilidad de testigos en el sistema penal acusatorio colombiano consagrado en la ley 906 de 2004, analiza algunos de sus aspectos problemáticos desde la perspectiva procesal y probatoria y expone los equívocos del concepto 'impugnación' en nuestro medio y su relación con la sana crítica.

  17. Computation of optimal transport and related hedging problems via penalization and neural networks

    OpenAIRE

    Eckstein, Stephan; Kupper, Michael

    2018-01-01

    This paper presents a widely applicable approach to solving (multi-marginal, martingale) optimal transport and related problems via neural networks. The core idea is to penalize the optimization problem in its dual formulation and reduce it to a finite dimensional one which corresponds to optimizing a neural network with smooth objective function. We present numerical examples from optimal transport, martingale optimal transport, portfolio optimization under uncertainty and generative adversa...

  18. Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

    Directory of Open Access Journals (Sweden)

    Fonseca Carlos M

    2010-10-01

    Full Text Available Abstract Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the

  19. Multiple Response Regression for Gaussian Mixture Models with Known Labels.

    Science.gov (United States)

    Lee, Wonyul; Du, Ying; Sun, Wei; Hayes, D Neil; Liu, Yufeng

    2012-12-01

    Multiple response regression is a useful regression technique to model multiple response variables using the same set of predictor variables. Most existing methods for multiple response regression are designed for modeling homogeneous data. In many applications, however, one may have heterogeneous data where the samples are divided into multiple groups. Our motivating example is a cancer dataset where the samples belong to multiple cancer subtypes. In this paper, we consider modeling the data coming from a mixture of several Gaussian distributions with known group labels. A naive approach is to split the data into several groups according to the labels and model each group separately. Although it is simple, this approach ignores potential common structures across different groups. We propose new penalized methods to model all groups jointly in which the common and unique structures can be identified. The proposed methods estimate the regression coefficient matrix, as well as the conditional inverse covariance matrix of response variables. Asymptotic properties of the proposed methods are explored. Through numerical examples, we demonstrate that both estimation and prediction can be improved by modeling all groups jointly using the proposed methods. An application to a glioblastoma cancer dataset reveals some interesting common and unique gene relationships across different cancer subtypes.

  20. Boosting structured additive quantile regression for longitudinal childhood obesity data.

    Science.gov (United States)

    Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

    2013-07-25

    Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

  1. Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

    Science.gov (United States)

    Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

    2012-07-01

    Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

  2. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  3. The Multivariate Gaussian Probability Distribution

    DEFF Research Database (Denmark)

    Ahrendt, Peter

    2005-01-01

    This technical report intends to gather information about the multivariate gaussian distribution, that was previously not (at least to my knowledge) to be found in one place and written as a reference manual. Additionally, some useful tips and tricks are collected that may be useful in practical ...

  4. A "Model" Multivariable Calculus Course.

    Science.gov (United States)

    Beckmann, Charlene E.; Schlicker, Steven J.

    1999-01-01

    Describes a rich, investigative approach to multivariable calculus. Introduces a project in which students construct physical models of surfaces that represent real-life applications of their choice. The models, along with student-selected datasets, serve as vehicles to study most of the concepts of the course from both continuous and discrete…

  5. Iluminismo e absolutismo no modelo jurídico-penal de Cesare Beccaria

    Directory of Open Access Journals (Sweden)

    Alexander de Castro

    2008-09-01

    Full Text Available Cesare Beccaria, tido como o autor que,elaborando um sistema de direito penal com base emprincípios iluministas, criou as bases do modernodireito penal de cunho liberal, possuía, entretanto,vínculos muito profundos com o absolutismo austríaco.Assim, no presente trabalho, analisaremosalguns pontos da tessitura política em que Beccariaproduziu a obra Dei Delitti e delle Pene, procurandoaprofundar a compreensão sobre o modo como oIluminismo, no contexto de formação do absolutismohabsbúrgico, funcionaria na elaboração do modelojurídico-penal do jurista italiano.Abstract: Cesare Beccaria, known as the authorwho, elaborating a system of criminal law basedon illuminists principles, has created the bases ofthe modern liberal criminal law, had, however, verydeep bonds with the Austrian absolutism. Thus,in the present paper, we will analyze some pointsof the politic structure where Beccaria producedhis work Dei Delitti e delle Pene, seeking to examinethe understanding about the way Illuminism,in the context of the Habsburg absolutism’sformation, would operate in the elaboration ofthe Italian jurist’s legal criminal model.

  6. La Intervención del Derecho Penal en Los Fenómenos Migratorios

    Directory of Open Access Journals (Sweden)

    Thamara Duarte Cunha Medeiros

    2016-06-01

    Full Text Available El presente artículo tiene por objetivo analisar la legitimidad de la intervención penal en los actuales flujos migratórios. La premisa principal considera que la utilización del derecho penal como instrumento de gestión para controlar flujos migratório ratifica el discurso del miedo hacia la inmingración y fomenta la criminalidad organizada que se ha estructurado frente a las políticas tolerancia cero contra la inmigración, especialmente, la trata de personas y el contrabando de migrantes. En este sentido, el analisis y la delimitación del bien jurídico “ política migratória” sugiere una reflexión a la luz de las bases principiológicas del Derecho Penal y despierta cuestiones que implican en una redefinición del derecho de punir en la sociedad del riesgo.

  7. A Postneoliberal Turn? Variants of the Recent Penal Policy in Argentina

    Directory of Open Access Journals (Sweden)

    Maximo Sozzo

    2017-03-01

    Full Text Available This paper analysed the connection between the emergence and consolidation of a postneoliberal political program and alliance – Kirchnerism – and penal policies in Argentina. Three key moments are identified in this recent period. After the experience of an intense punitive turn during the 1990s and early 2000s, Kirchnerist political alliances tried to deploy a progressive political discourse and agenda on penal issues. Nevertheless, this initially coincided with a strong wave of penal populism ‘from below’ that continued the precedent trend towards increasing punitiviness.  Since 2005, and for a brief moment, this tendency stopped. However, after that and during the presidencies of Fernandez de Kirchner a more volatile and contradictory scenario was generated. The incarceration rate between 2002 and 2014 in Argentina grew substantially as did the rate of convictions. Meanwhile the percentage of suspended sentences as part of the total convictions and the percentage of custodial sanctions both fell. Especially in relation to incarceration, these levels of change are not as stark as those of the preceding decades. However, the trends persist. Therefore, the question of how to transcend the dynamics of the punitive turn remains a pending and urgent political subject. The article argues the importance of analysing why a punitive turn is interrupted and presents an explanation of it.

  8. El garantismo y el punitivismo en el Código Orgánico Integral Penal

    Directory of Open Access Journals (Sweden)

    Sebastián Cornejo Aguiar

    2016-12-01

    Full Text Available El objetivo del presente artículo es determinar la necesidad de la existencia de una parte punitivista y una garantista dentro del Código Orgánico Integral Penal, partiendo del estudio de la actualización doctrinaria en materia penal dentro del ordenamiento jurídico ecuatoriano, considerando que al ser el Ecuador un Estado constitucional de derechos y justicia, nos inspira a la construcción de mecanismos que tengan como fundamento y fin la tutela de las libertades del individuo, frente a las variadas formas del ejercicio arbitrario del poder punitivo del Estado, en donde las garantías y principios establecidos en el Código Orgánico Integral Penal, deben ser considerados como filtros de contención del poder punitivo que impiden que dicho poder se desborde y destruya todo a su paso. Seguidamente se analiza el significado del garantismo y punitivismo. Por último, se toca la relación existente entre garantismo y punitivismo, concluyendo que el garantismo es una corriente que proporciona ideas sustanciales para transformar el procedimiento judicial impidiendo así la arbitrariedad del poder punitivo.

  9. A second order penalized direct forcing for hybrid Cartesian/immersed boundary flow simulations

    International Nuclear Information System (INIS)

    Introini, C.; Belliard, M.; Fournier, C.

    2014-01-01

    In this paper, we propose a second order penalized direct forcing method to deal with fluid-structure interaction problems involving complex static or time-varying geometries. As this work constitutes a first step toward more complicated problems, our developments are restricted to Dirichlet boundary condition in purely hydraulic context. The proposed method belongs to the class of immersed boundary techniques and consists in immersing the physical domain in a Cartesian fictitious one of simpler geometry on fixed grids. A penalized forcing term is added to the momentum equation to take the boundary conditions around/inside the obstacles into account. This approach avoids the tedious task of re-meshing and allows us to use fast and accurate numerical schemes. In contrary, as the immersed boundary is described by a set of Lagrangian points that does not generally coincide with those of the Eulerian grid, numerical procedures are required to reconstruct the velocity field near the immersed boundary. Here, we develop a second order linear interpolation scheme and we compare it to a simpler model of order one. As far as the governing equations are concerned, we use a particular fractional-step method in which the penalized forcing term is distributed both in prediction and correction equations. The accuracy of the proposed method is assessed through 2-D numerical experiments involving static and rotating solids. We show in particular that the numerical rate of convergence of our method is quasi-quadratic. (authors)

  10. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  11. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

  12. The cross-validated AUC for MCP-logistic regression with high-dimensional data.

    Science.gov (United States)

    Jiang, Dingfeng; Huang, Jian; Zhang, Ying

    2013-10-01

    We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

  13. Una apuesta analítica del funcionamiento del dispositivo psi pericial en el campo penal Uma aposta analitica do funcionamento do dispositivo psi pericial inserido no campo penal An analysis of the psy expert assemblage in the penal field

    Directory of Open Access Journals (Sweden)

    Laura López Gallego

    2010-08-01

    Full Text Available La aproximación al dispositivo psi pericial inserto en el campo penal aquí efectuada, traza un itinerario de análisis que aborda el funcionamiento de dicho dispositivo, poniendo especial énfasis en las imbricadas relaciones entre los saberes jurídicos y lo psi. Para efectuar dicho análisis, se utilizan documentos específicos producidos por los peritos psi en el marco del Poder Judicial del Uruguay. Se entiende a las prácticas psi como el efecto de ciertas confluencias históricas relacionadas con el examen, con las estrategias de objetividad, con la traducción de categorías psi en categorías jurídicas y con la incorporación de la lógica de individualización como eje del dispositivo psi pericial. La pregunta que guía el análisis versa sobre lo que posibilita la incorporación del dispositivo psi pericial en el campo penal.A aproximação ao dispositivo psi pericial inserido no campo penal aqui realizada traça um itinerário de análise que aborda o funcionamento do dispositivo, enfatizando as relações imbricadas entre os saberes jurídicos e psi. Para realizar a análise, utilizam-se documentos específicos produzidos por peritos psi no marco do Poder Judicial do Uruguai. Entendem-se as práticas psi como efeito de certas confluências históricas relacionadas ao exame, às estratégias de objetividade, à tradução de categorias psi em categorias jurídicas e à incorporação da lógica da individualização como um ponto central do dispositivo psi pericial. A pergunta que orienta a análise é o que possibilita a incorporação do dispositivo psi pericial no campo penal.The approach made here about the "expert psy assemblage" inserted into the criminal field draws a path of analysis that considers the operation of this assemblage, highlighting the intertwined relationships between the legal and psychological knowledge. To undertake such analysis, specific documents produced by the psy experts, working under the Judiciary

  14. Multiple linear regression analysis

    Science.gov (United States)

    Edwards, T. R.

    1980-01-01

    Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

  15. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  16. Linear Regression Analysis

    CERN Document Server

    Seber, George A F

    2012-01-01

    Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

  17. Nonlinear Regression with R

    CERN Document Server

    Ritz, Christian; Parmigiani, Giovanni

    2009-01-01

    R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.

  18. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. Bounded Gaussian process regression

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

    2013-01-01

    We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....

  20. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  1. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  2. Bayesian nonlinear regression for large small problems

    KAUST Repository

    Chakraborty, Sounak; Ghosh, Malay; Mallick, Bani K.

    2012-01-01

    Statistical modeling and inference problems with sample sizes substantially smaller than the number of available covariates are challenging. This is known as large p small n problem. Furthermore, the problem is more complicated when we have multiple correlated responses. We develop multivariate nonlinear regression models in this setup for accurate prediction. In this paper, we introduce a full Bayesian support vector regression model with Vapnik's ε-insensitive loss function, based on reproducing kernel Hilbert spaces (RKHS) under the multivariate correlated response setup. This provides a full probabilistic description of support vector machine (SVM) rather than an algorithm for fitting purposes. We have also introduced a multivariate version of the relevance vector machine (RVM). Instead of the original treatment of the RVM relying on the use of type II maximum likelihood estimates of the hyper-parameters, we put a prior on the hyper-parameters and use Markov chain Monte Carlo technique for computation. We have also proposed an empirical Bayes method for our RVM and SVM. Our methods are illustrated with a prediction problem in the near-infrared (NIR) spectroscopy. A simulation study is also undertaken to check the prediction accuracy of our models. © 2012 Elsevier Inc.

  3. Bayesian nonlinear regression for large small problems

    KAUST Repository

    Chakraborty, Sounak

    2012-07-01

    Statistical modeling and inference problems with sample sizes substantially smaller than the number of available covariates are challenging. This is known as large p small n problem. Furthermore, the problem is more complicated when we have multiple correlated responses. We develop multivariate nonlinear regression models in this setup for accurate prediction. In this paper, we introduce a full Bayesian support vector regression model with Vapnik\\'s ε-insensitive loss function, based on reproducing kernel Hilbert spaces (RKHS) under the multivariate correlated response setup. This provides a full probabilistic description of support vector machine (SVM) rather than an algorithm for fitting purposes. We have also introduced a multivariate version of the relevance vector machine (RVM). Instead of the original treatment of the RVM relying on the use of type II maximum likelihood estimates of the hyper-parameters, we put a prior on the hyper-parameters and use Markov chain Monte Carlo technique for computation. We have also proposed an empirical Bayes method for our RVM and SVM. Our methods are illustrated with a prediction problem in the near-infrared (NIR) spectroscopy. A simulation study is also undertaken to check the prediction accuracy of our models. © 2012 Elsevier Inc.

  4. Robust methods for multivariate data analysis A1

    DEFF Research Database (Denmark)

    Frosch, Stina; Von Frese, J.; Bro, Rasmus

    2005-01-01

    Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...

  5. CONTRADICTORIALITATEA ÎN CORAPORT CU ALTE PRINCIPII ALE PROCESULUI PENAL

    Directory of Open Access Journals (Sweden)

    Lucia RUSU

    2016-03-01

    Full Text Available În legătură cu reformarea sistemului judiciar şi schimbările intervenite în viaţa social-politică a statului nostru, prin­cipiul contradictorialităţii a obţinut o nouă rezonanţă din considerentul că reforma judiciară şi de drept este legată direct de contradictorialitate. Reforma legii procesual penale trebuie să fie fundamentată pe o temelie teoretică solidă. Contra­dictorialitatea, însă, în calitate de noţiune juridică, este insuficient cercetată în doctrina dreptului procesual penal. La ziua de azi, specialişti notorii în domeniul dreptului procesual penal analizează şi studiază importanţa fundamentelor şi principiilor de bază ale procesului penal şi, în primul rând, contradictorialitatea acestuia. Legea procesual penală a Republicii Moldova cunoaşte o evoluţie şi dezvoltate în sensul democratizării şi lărgirii începuturilor contradictoriale în înfăptuirea justiţiei. Aceasta e şi firesc, deoarece contradictorialitatea are o importanţă enormă pentru întregul sistem al procesului penal, determinând în mare parte statutul juridic şi raporturile dintre participanţii la procesul penal, precum şi relaţiile juridice stabilite între participanţii la acest proces şi instanţa de judecată. CONTRADICTION AND ITS CORRELATION WITH OTHER PRINCIPLES OF THE CRIMINAL PROCEEDINGIn connection with the judiciary system reforming and changes in socio-political life of our state, the adversarial principle has gained a new resonance on the grounds that the judicial and legal reform is directly linked to adversariality. The reform of the criminal procedure law must be based on solid theoretical foundation. However, adversariality, as legal concept, is not enough investigated in the doctrine of the criminal procedure law. Currently, notorious specialists in the field of criminal procedure law examine and study the importance of fundamentals and basic principles of the criminal process and

  6. Descriptor Learning via Supervised Manifold Regularization for Multioutput Regression.

    Science.gov (United States)

    Zhen, Xiantong; Yu, Mengyang; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo

    2017-09-01

    Multioutput regression has recently shown great ability to solve challenging problems in both computer vision and medical image analysis. However, due to the huge image variability and ambiguity, it is fundamentally challenging to handle the highly complex input-target relationship of multioutput regression, especially with indiscriminate high-dimensional representations. In this paper, we propose a novel supervised descriptor learning (SDL) algorithm for multioutput regression, which can establish discriminative and compact feature representations to improve the multivariate estimation performance. The SDL is formulated as generalized low-rank approximations of matrices with a supervised manifold regularization. The SDL is able to simultaneously extract discriminative features closely related to multivariate targets and remove irrelevant and redundant information by transforming raw features into a new low-dimensional space aligned to targets. The achieved discriminative while compact descriptor largely reduces the variability and ambiguity for multioutput regression, which enables more accurate and efficient multivariate estimation. We conduct extensive evaluation of the proposed SDL on both synthetic data and real-world multioutput regression tasks for both computer vision and medical image analysis. Experimental results have shown that the proposed SDL can achieve high multivariate estimation accuracy on all tasks and largely outperforms the algorithms in the state of the arts. Our method establishes a novel SDL framework for multioutput regression, which can be widely used to boost the performance in different applications.

  7. Ridge Regression Signal Processing

    Science.gov (United States)

    Kuhl, Mark R.

    1990-01-01

    The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

  8. Subset selection in regression

    CERN Document Server

    Miller, Alan

    2002-01-01

    Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

  9. On generalized elliptical quantiles in the nonlinear quantile regression setup

    Czech Academy of Sciences Publication Activity Database

    Hlubinka, D.; Šiman, Miroslav

    2015-01-01

    Roč. 24, č. 2 (2015), s. 249-264 ISSN 1133-0686 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * elliptical quantile * quantile regression * multivariate statistical inference * portfolio optimization Subject RIV: BA - General Mathematics Impact factor: 1.207, year: 2015 http://library.utia.cas.cz/separaty/2014/SI/siman-0434510.pdf

  10. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  11. Regression in organizational leadership.

    Science.gov (United States)

    Kernberg, O F

    1979-02-01

    The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.

  12. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  13. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  14. Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

    International Nuclear Information System (INIS)

    Dyar, M.D.; Carmosino, M.L.; Breves, E.A.; Ozanne, M.V.; Clegg, S.M.; Wiens, R.C.

    2012-01-01

    A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the

  15. Comparison of partial least squares and lasso regression techniques as applied to laser-induced breakdown spectroscopy of geological samples

    Energy Technology Data Exchange (ETDEWEB)

    Dyar, M.D., E-mail: mdyar@mtholyoke.edu [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Carmosino, M.L.; Breves, E.A.; Ozanne, M.V. [Dept. of Astronomy, Mount Holyoke College, 50 College St., South Hadley, MA 01075 (United States); Clegg, S.M.; Wiens, R.C. [Los Alamos National Laboratory, P.O. Box 1663, MS J565, Los Alamos, NM 87545 (United States)

    2012-04-15

    A remote laser-induced breakdown spectrometer (LIBS) designed to simulate the ChemCam instrument on the Mars Science Laboratory Rover Curiosity was used to probe 100 geologic samples at a 9-m standoff distance. ChemCam consists of an integrated remote LIBS instrument that will probe samples up to 7 m from the mast of the rover and a remote micro-imager (RMI) that will record context images. The elemental compositions of 100 igneous and highly-metamorphosed rocks are determined with LIBS using three variations of multivariate analysis, with a goal of improving the analytical accuracy. Two forms of partial least squares (PLS) regression are employed with finely-tuned parameters: PLS-1 regresses a single response variable (elemental concentration) against the observation variables (spectra, or intensity at each of 6144 spectrometer channels), while PLS-2 simultaneously regresses multiple response variables (concentrations of the ten major elements in rocks) against the observation predictor variables, taking advantage of natural correlations between elements. Those results are contrasted with those from the multivariate regression technique of the least absolute shrinkage and selection operator (lasso), which is a penalized shrunken regression method that selects the specific channels for each element that explain the most variance in the concentration of that element. To make this comparison, we use results of cross-validation and of held-out testing, and employ unscaled and uncentered spectral intensity data because all of the input variables are already in the same units. Results demonstrate that the lasso, PLS-1, and PLS-2 all yield comparable results in terms of accuracy for this dataset. However, the interpretability of these methods differs greatly in terms of fundamental understanding of LIBS emissions. PLS techniques generate principal components, linear combinations of intensities at any number of spectrometer channels, which explain as much variance in the

  16. Use of multivariate extensions of generalized linear models in the analysis of data from clinical trials

    OpenAIRE

    ALONSO ABAD, Ariel; Rodriguez, O.; TIBALDI, Fabian; CORTINAS ABRAHANTES, Jose

    2002-01-01

    In medical studies the categorical endpoints are quite often. Even though nowadays some models for handling this multicategorical variables have been developed their use is not common. This work shows an application of the Multivariate Generalized Linear Models to the analysis of Clinical Trials data. After a theoretical introduction models for ordinal and nominal responses are applied and the main results are discussed. multivariate analysis; multivariate logistic regression; multicategor...

  17. Teoria da adequação econômica da conduta: significado econômico da conduta em face da tutela penal antitruste

    OpenAIRE

    Luiz da Silva, Ivan

    2009-01-01

    Essa tese tem por objetivo o desenvolvimento da teoria da adequação econômica da conduta no direito penal econômico. Vale-se de uma abordagem interdisciplinar abrangendo a Economia, o direito econômico e o direito penal. Para alcançar o desiderato a investigação analisou a intervenção do direito penal em face da atividade econômica e, em especial, os fundamentos da tutela penal antitruste, para fins de estabelecer os contornos teóricos necessários à aplicação das premissas fund...

  18. EVOLUCIÓN CRIMINOLÓGICA, PENAL Y PENITENCIARIA EN CATALUÑA DESDE LA REFORMA DEL CÓDIGO PENAL DE 1995. ESTUDIO ESTADÍSTICO-DESCRIPTIVO.

    Directory of Open Access Journals (Sweden)

    Josep García-Borés Espí

    2015-10-01

    Full Text Available El presente artículo surge como resultado de la recopilación de datos llevada a cabo por el equipo investigador del Observatorio del Sistema Penal y los Derechos Humanos de la Universidad de Barcelona (OSPDH, en el marco de la investigación: “¿Resocialización o incapacitación?: Sostenibilidad del Sistema Penitenciario español ante las nuevas realidades delictivas y demandas de seguridad”[1]. A lo largo del proceso de recogida de información el equipo investigador del OSPDH, fue constatando la existencia de evidencias estadísticas que ponían de manifiesto la evolución y los cambios experimentados en el sistema penitenciario catalán durante los últimos veinte años, identificándose una estrecha relación entre los mismos y los diversos periodos político-económicos vividos en el conjunto del Estado español desde la reforma del Código Penal de1995 hasta la actualidad[2]. [1] El presente trabajo se ha realizado en el marco del Proyecto de Investigación  I+D+i: "¿RESOCIALIZACIÓN O INCAPACITACIÓN? SOSTENIBILIDAD DEL SISTEMA PENITENCIARIO ESPAÑOL ANTE LAS NUEVAS REALIDADES DELICTIVAS Y DEMANDAS DE SEGURIDAD, con referencia DER2011-27337, del Ministerio de Economía y Competitividad.   [2] Periodos que son desarrollados en este mismo Monográfico en el artículo de Brandariz (2015, titulado: La evolución del sistema penitenciario español, 1995-2014: transformaciones de la penalidad y modificación práctica de la realidad penitenciaria.

  19. Sparse Regression by Projection and Sparse Discriminant Analysis

    KAUST Repository

    Qi, Xin

    2015-04-03

    © 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

  20. Evolución del Derecho penal en el ámbito internacional. Pluralismo y garantismo jurídico-penal como criterios orientadores || Evolution Of The Supranational Criminal Law: Pluralism And Protection Of The Civil Liberties As Guiding Criteria

    Directory of Open Access Journals (Sweden)

    Jorge Correcher Mira

    2013-12-01

    Full Text Available RESUMEN La realidad social internacional presenta un nuevo paradigma que debe ser asumido por el Derecho penal. El contexto social internacional, marcado por la globalización a nivel mundial y el proceso de integración europea en el ámbito comunitario, supone una modificación de las líneas clásicas de recepción de las normas penales, demandando un tratamiento supraestatal del sistema penal. En este trabajo, se analiza desde una perspectiva crítica las propuestas de internacionalización del Derecho penal, en la medida que éstas no han seguido nociones como el pluralismo jurídico y el carácter garantista inherente al Derecho penal.   ABSTRACT The social international reality presents a new paradigm that must be taken up office for the Criminal law. The social international context, marked by the globalization worldwide and the process of European integration in the European area, supposes a modification of the classic lines of receipt of the Criminal law, demanding a supranational treatment of the Criminal System. In this work, the offers of internationalize the Criminal Law will be analyzed from a critical point of view, cause these have not followed notions as the juridical pluralism and the protection of civil liberties inherent in the Criminal Law.

  1. Evolución del Derecho penal en el ámbito internacional. Pluralismo y garantismo jurídico-penal como criterios orientadores || Evolution Of The Supranational Criminal Law: Pluralism And Protection Of The Civil Liberties As Guiding Criteria

    Directory of Open Access Journals (Sweden)

    Jorge Correcher Mira

    2013-12-01

    Full Text Available RESUMEN La realidad social internacional presenta un nuevo paradigma que debe ser asumido por el Derecho penal. El contexto social internacional, marcado por la globalización a nivel mundial y el proceso de integración europea en el ámbito comunitario, supone una modificación de las líneas clásicas de recepción de las normas penales, demandando un tratamiento supraestatal del sistema penal. En este trabajo, se analiza desde una perspectiva crítica las propuestas de internacionalización del Derecho penal, en la medida que éstas no han seguido nociones como el pluralismo jurídico y el carácter garantista inherente al Derecho penal.   ABSTRACT The social international reality presents a new paradigm that must be taken up office for the Criminal law. The social international context, marked by the globalization worldwide and the process of European integration in the European area, supposes a modification of the classic lines of receipt of the Criminal law, demanding a supranational treatment of the Criminal System. In this work, the offers of internationalize the Criminal Law will be analyzed from a critical point of view, cause these have not followed notions as the juridical pluralism and the protection of civil liberties inherent in the Criminal Law.  

  2. Numerical discretization-based estimation methods for ordinary differential equation models via penalized spline smoothing with applications in biomedical research.

    Science.gov (United States)

    Wu, Hulin; Xue, Hongqi; Kumar, Arun

    2012-06-01

    Differential equations are extensively used for modeling dynamics of physical processes in many scientific fields such as engineering, physics, and biomedical sciences. Parameter estimation of differential equation models is a challenging problem because of high computational cost and high-dimensional parameter space. In this article, we propose a novel class of methods for estimating parameters in ordinary differential equation (ODE) models, which is motivated by HIV dynamics modeling. The new methods exploit the form of numerical discretization algorithms for an ODE solver to formulate estimating equations. First, a penalized-spline approach is employed to estimate the state variables and the estimated state variables are then plugged in a discretization formula of an ODE solver to obtain the ODE parameter estimates via a regression approach. We consider three different order of discretization methods, Euler's method, trapezoidal rule, and Runge-Kutta method. A higher-order numerical algorithm reduces numerical error in the approximation of the derivative, which produces a more accurate estimate, but its computational cost is higher. To balance the computational cost and estimation accuracy, we demonstrate, via simulation studies, that the trapezoidal discretization-based estimate is the best and is recommended for practical use. The asymptotic properties for the proposed numerical discretization-based estimators are established. Comparisons between the proposed methods and existing methods show a clear benefit of the proposed methods in regards to the trade-off between computational cost and estimation accuracy. We apply the proposed methods t an HIV study to further illustrate the usefulness of the proposed approaches. © 2012, The International Biometric Society.

  3. Steganalysis using logistic regression

    Science.gov (United States)

    Lubenko, Ivans; Ker, Andrew D.

    2011-02-01

    We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

  4. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  5. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...

  6. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.

    2015-01-01

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  7. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...

  8. Improved multivariate polynomial factoring algorithm

    International Nuclear Information System (INIS)

    Wang, P.S.

    1978-01-01

    A new algorithm for factoring multivariate polynomials over the integers based on an algorithm by Wang and Rothschild is described. The new algorithm has improved strategies for dealing with the known problems of the original algorithm, namely, the leading coefficient problem, the bad-zero problem and the occurrence of extraneous factors. It has an algorithm for correctly predetermining leading coefficients of the factors. A new and efficient p-adic algorithm named EEZ is described. Bascially it is a linearly convergent variable-by-variable parallel construction. The improved algorithm is generally faster and requires less store then the original algorithm. Machine examples with comparative timing are included

  9. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaël

    2015-11-17

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  10. Simulation of multivariate diffusion bridges

    DEFF Research Database (Denmark)

    Bladt, Mogens; Finch, Samuel; Sørensen, Michael

    We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental role in simulation-based likelihood and Bayesian inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes a previously...... proposed simulation method for one-dimensional bridges to the mulit-variate setting. First a method of simulating approzimate, but often very accurate, diffusion bridges is proposed. These approximate bridges are used as proposal for easily implementable MCMC algorithms that produce exact diffusion bridges...

  11. Essentials of multivariate data analysis

    CERN Document Server

    Spencer, Neil H

    2013-01-01

    ""… this text provides an overview at an introductory level of several methods in multivariate data analysis. It contains in-depth examples from one data set woven throughout the text, and a free [Excel] Add-In to perform the analyses in Excel, with step-by-step instructions provided for each technique. … could be used as a text (possibly supplemental) for courses in other fields where researchers wish to apply these methods without delving too deeply into the underlying statistics.""-The American Statistician, February 2015

  12. Multivariate process monitoring of EAFs

    Energy Technology Data Exchange (ETDEWEB)

    Sandberg, E.; Lennox, B.; Marjanovic, O.; Smith, K.

    2005-06-01

    Improved knowledge of the effect of scrap grades on the electric steelmaking process and optimised scrap loading practices increase the potential for process automation. As part of an ongoing programme, process data from four Scandinavian EAFs have been analysed, using the multivariate process monitoring approach, to develop predictive models for end point conditions such as chemical composition, yield and energy consumption. The models developed generally predict final Cr, Ni and Mo and tramp element contents well, but electrical energy consumption, yield and content of oxidisable and impurity elements (C, Si, Mn, P, S) are at present more difficult to predict. Potential scrap management applications of the prediction models are also presented. (author)

  13. Aspects of multivariate statistical theory

    CERN Document Server

    Muirhead, Robb J

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "". . . the wealth of material on statistics concerning the multivariate normal distribution is quite exceptional. As such it is a very useful source of information for the general statistician and a must for anyone wanting to pen

  14. Derecho penal, cyberbullying y otras formas de acoso (no sexual en el ciberespacio

    Directory of Open Access Journals (Sweden)

    Fernando Miró Llinares

    2013-06-01

    Full Text Available

    Las redes sociales, en particular, e internet en general, constituyen hoy en día un nuevo ámbito de desarrollo personal, un nuevo espacio vital en el que cada individuo pasa varias horas al día, se comunica con otros, crea relaciones, y en el que, por tanto, también se cometen ataques contra bienes individuales como el honor, la libertad, la intimidad o la propia dignidad personal. En el presente trabajo se analiza la respuesta del ordenamiento penal español a las distintas formas de acoso no sexual a menores realizado en el ciberespacio. A partir de la descripción y conceptualización de fenómenos como el cyberbullying, o los actos individuales de online harassment, se analiza la concreta incardinación de las distintas modalidades de acoso, continuado o no, a menores, en los diferentes tipos de la parte especial. Al no existir un precepto penal que regule expresamente la mayoría de estas conductas, y pese a haberse convertido el tipo básico de los delitos contra la integridad moral en el delito de referencia para los tribunales, son varios (amenazas, coacciones, injurias, etc. los tipos penales que pueden aplicarse en conductas de acoso, generalmente entre iguales, que, como se verá por el amplísimo repertorio jurisprudencial, están comenzando a proliferar en el ciberespacio.

  15. De víctimas a victimarios: sobre la racionalidad mediática-penal

    Directory of Open Access Journals (Sweden)

    Manchado, Mauricio Carlos

    2017-01-01

    Full Text Available [es] En el presente trabajo nos proponemos, como objetivo general, indagar sobre las construcciones mediáticas en torno a la figura del “individuo peligroso” en el discurso de la prensa gráfica local, tomando como caso de análisis el Diario La Capital de Rosario. Para ello, procuraremos describir un procedimiento discursivo singular en el relato mediático a raíz de los resultados de nuestro trabajo de campo: la víctima de un delito, en caso de tener antecedentes penales, será configurado como victimario. Operación discursiva que cristaliza una de las tantas manifestaciones de una racionalidad mediática-penal neoliberal donde por una parte, se condena justificando la muerte de la víctima por pertenecer a un sector social que no merece vivir y por otro, construye la figura de una víctima que pronto será victimario de si-mismo. [en] In this paper we propose, as a general objective, inquiring about media constructions around the figure of the “dangerous individual” in the discoruse of local press media, taking the case of the newspaper La Capital of Rosario. For that, we will describe a singular process: if a victim of crime have criminal records, will be configured as a victimizer. Discursive operation that cristalice one of the many manifestations of a neo-liberal-penal-media rationality where on the one hand, condemn justifying the death of the victim for belong to a social sector that does not deserve to live and on the other, builds the victim figure that will be soon a victimizer of himself.

  16. The convict’s family as a participant in his penal resocialisation, readaptation and social reintegration

    Directory of Open Access Journals (Sweden)

    Henryk Machel

    2014-06-01

    Full Text Available One of the elements of penal social rehabilitation procedure is maintaining social ties with criminal’s families. The family bonds of criminal, maintained at an appropriate level, provide the basis for social re-processing, and for safeguarding criminals, freed conditionally or at the end of their sentences, from reoffending. Maintaining proper social ties between inmates and their families is essential for the proper process of penal reintegration and its end effect. The social bonds of prisoners can be classified according to the length of the sentence and depend on the type of sentence. If there is no family relationship (e.g. when someone is serving a sentence for an offense against their family it is not possible to use it in the social rehabilitation process. Weak familial bonds can be reconstructed and treated as one of the process’s important objectives. A strong familial bond can and should be used to support and strengthen that process. The family bond is felt somewhat differently by women (the issue is concern for children, fear of abandonment by life partners, etc. than by men. However, with regard to both categories of convicts, it plays an important role in the process of their rehabilitation and social re-adjustment, and helps prevent stigma. The recommended way of using good family relationships and rebuilding poor ties in penal work was applied with a positive effect for 20 months in a measured social rehabilitation experiment devised by the author, organised and implemented in a prison in Gdańsk-Przeróbka until the introduction of martial law in Poland in 1981. It was very positively evaluated by J. Rejman in his book entitled Change in the Polish penitentiary system – constraints and opportunities, published in 2013. The system operated throughout the entire prison facility and, as noted, was effective both in resocialisation and rehabilitation.

  17. Problems of causality in environmental penal law. The relevance of causality problems on the environmental sector from the view of penal law. Kausalitaetsprobleme im Umweltstrafrecht. Die strafrechtliche Relevanz der Schwierigkeiten naturwissenschaftlicher Kausalfeststellung im Umweltbereich

    Energy Technology Data Exchange (ETDEWEB)

    Kleine-Cosack, E.

    1988-01-01

    The 'classic' elements of an offence against human health or property are not applicable in environmental law, owing to problems of causality. The new environmental penal law therefore focuses on the 'capability' of any act to damage human health, animal health, vegetation, water, air, or soil. It remarks doubtful whether this approach is more efficient. Further, there is still the problem of assessing damage. The book discusses causality problems in environmental penal law. Causality in a given case is discussed from the view of general causality laws and problems of proof. Other possible causes of damage must be excluded. The author discusses: Interdependences between scientific and penal causality, the problems of successful and potential offences, the relationship between individual and universal objects of legal protection, and procedural issues (e.g. the binding effect of experts' opinions on a given subject). (orig./HSCH).

  18. BIOÉTICA, TRASPLANTE DE ÓRGANOS Y DERECHO PENAL EN COLOMBIA

    Directory of Open Access Journals (Sweden)

    Yolanda M. Guerra García

    2011-01-01

    Full Text Available Este artículo presenta los lineamientos del Derecho Penal que trascienden los conceptos de trasplantes de órganos y las implicaciones Bioéticas de los mismos. Del mismo modo se establecen algunos de los principales criterios relacionados con el debate bioético en torno al problema de la Donación y Trasplante de Órganos, problemas relacionados con temas como la Muerte Encefálica, el consentimiento informado, Justicia y Distribución, los Xenotrasplantes y la Clonación Embrionaria entre otros.

  19. Violencia de género en la familia: perspectiva jurídico penal

    OpenAIRE

    José Julio Nares Hernández; Dulce Gloria Martínez García; Ricardo Colín García

    2015-01-01

    Se analizan desde una perspectiva garantista la Constitución Federal y los tratados internacionales que obligan al Estado a tutelar penalmente el derecho humano de la mujer a una vida libre de violencia en el hogar. Se concluye que para cumplir con este deber es ineludible la creación legislativa de tipo penal que sancione la violencia familiar asociada a la violencia de género. Esta acción legislativa sería parte de una nueva política criminológica dedicada específicamente a la prevención, s...

  20. Acusación Pública e Instrucción del Procedimiento Penal

    OpenAIRE

    Alfonso Rodríguez, Adriano Jacinto

    2015-01-01

    El Ministerio Fiscal es un elemento esencial dentro de nuestro ordenamiento jurídico. Sin embargo carece de un papel claro dentro de nuestro esquema de justicia penal. Por otro lado, el Juez de Instrucción no cumple adecuadamente con su papel de garante dentro de nuestro sistema precisamente por su doble papel de garante e investigador. Por tanto es necesario un cambio que sitúe a cada sujeto en el lugar que le corresponde para tener un procedimiento más garantista en el que cada uno cumpla c...

  1. Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.

    Science.gov (United States)

    Becker, Natalia; Toedt, Grischa; Lichter, Peter; Benner, Axel

    2011-05-09

    Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error.Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters.The penalized SVM

  2. La protección del bienestar animal a través del Derecho Penal

    OpenAIRE

    Hava García, Esther

    2011-01-01

    El presente artículo analiza la influencia que los movimientos animalistas están teniendo en el reconocimiento de un estándar de protección a los animales en el ordenamiento jurídico. Tras exponer las principales normas que regulan el bienestar animal en el Derecho europeo y en el Derecho administrativo español, así como la evolución que en los últimos años ha experimentado la tutela penal de los animales, se trata de concretar el bien jurídico protegido tanto en el delito d...

  3. Nicaragua en proceso de creación de Código Procesal Penal

    Directory of Open Access Journals (Sweden)

    César Barrientos Pellecer

    2000-08-01

    Full Text Available En la elaboración de un Código Procesal Penal, Nicaragua puede hacer acopio de toda la experiencia regional, para avanzar a la sencillez y simplificación de formas y etapas procesales, mediante procedimientos ágiles que no impliquen grandes inversiones, y se apliquen de manera gradual, sin afectar los derechos del imputado, la víctima y la sociedad. También cuenta el país con los recursos humanos suficientes y calificados para elaborar una legislación capaz de enriquecer el desarrollo latinoamericano del sistema acusatorio.

  4. Modern environmental penal law in the light of the jurisdiction - review and tasks

    International Nuclear Information System (INIS)

    Rengier, R.

    1992-01-01

    The jurisdiction in modern environmental penal law has gone beyond just adopting the ecological tenets of the legislature: it has farthered their development, thus contributing substantially to an ecologically oriented understanding of the offences of water pollution and ecologically harmful waste disposal. This orientation has made prosecution more efficient and through its preventive effects has increased ecological awareness. A good example within the sphere of public interest are communal plant operators. In other areas such as private business and private households the preventive effect is not yet as apparent, but this will probably change in the course of time. (orig.) [de

  5. Elementos de la soberanía y del tribunal penal internacional

    OpenAIRE

    Scalquette, Rodrigo Arnoni

    2007-01-01

    Com o título de Elementos da Soberania e do Tribunal Penal Internacional procuramos demonstrar a ligação e pontos conflitantes entre o poder soberano e a Corte Internacional Criminal. No capítulo I, abordamos o conceito de soberania e seu enfoque de concepção política, realizado por Jean Bodin. Vimos o Estado-Leviatã de Thomas Hobbes e a soberania inalienável e indivisível de Jean-Jacques Rousseau. A relação entre Umberto Campagnolo e seu professor, Hans Kelsen, também foi abordada, nota...

  6. La implantación del Sistema Penal Acusatorio en Colombia: Un estudio multidisciplinario

    Directory of Open Access Journals (Sweden)

    Alfonso Reyes A

    2005-11-01

    Full Text Available El Acto Legislativo No. 03 del 19 de diciembre de 2002 modificó la Constitución de 1991 y estableció el Sistema Penal Acusatorio en Colombia. Este es, tal vez, el cambio más complejo sufrido en la administración de justicia durante la última década. La implantación del nuevo sistema implicaba modificaciones de fondo en la rama judicial, la defensoría penal pública, la fiscalía general de la nación y los órganos de policía judicial. Para diseñar el detalle del proceso de cambio, la Comisión Interinstitucional para la Implantación del Sistema Penal Acusatorio abrió un concurso público que fue adjudicado a la Universidad de los Andes en unión temporal con el Instituto Ser de Investigación. Este artículo presenta un escueto recuento de la forma en que se desarrolló este trabajo multidisciplinario dirigido desde el Departamento de Ingeniería Industrial. / On December 19th 2002 the accusatory system was formally introduced in the Colombian Constitution. This is, perhaps, the most complex change that our judicial system has undergone in the last decade. The implementation of the new criminal system implied a profound change in several institutions: a the criminal courts, b the general prosecution office; c the national defense office; and d all other state agencies that support criminal investigations. In order to design this transition the Comisión Interinstitucional para la Implantación del Sistema Penal Acusatorio (a governmental Commission responsible for the implementation of the accusatory system open up a bidding. Uniandes in a temporal Union with the Instituto SER de Investigación, won this call for tenders. This paper briefly describes the way this multidisciplinary effort was done under the direction of the industrial engineering department.

  7. Tutela penal de la vida humana y política criminal. Aborto y eutanasia

    OpenAIRE

    Gutiérrez Gutiérrez, María Angélica

    2015-01-01

    Al ser la vida humana el derecho fundamental más importante, su tutela penal se ha llevado a cabo históricamente y en la actualidad, con mayor o menor intensidad, en todos los ordenamientos jurídicos del mundo. Dentro de la protección del derecho a la vida, mediante la tipificación del delito de homicidio y de asesinato, con sus distintas modalidades, nos encontramos con dos figuras jurídicas controvertidas por estar estrechamente vinculadas con la moral y, consiguientemente, por tener mucha ...

  8. Aproximación al estudio de la criminalidad y el derecho penal ambiental peruano

    Directory of Open Access Journals (Sweden)

    Pierre Foy Valencia

    1992-12-01

    Full Text Available   El presente estudio pretende esbozar algunos criterio u orientaciones para una aproximación crítica en relación con las actuales prácticas sociales que afectan o transgreden gravemente un conjunto de valores ambientales, valores pasibles de ser tutelados desde nuestro sistema de control penal. En ese sentido, se postula la necesidad de formular un modelo de análisis sistémico que integre los diferentes componentes que guardan relación con el fenómeno de la criminalidad contemporánea, en su variante ambiental.

  9. Credibility of psychological and psychiatric skilled procedures made to offended minors within penal procedures

    OpenAIRE

    Mena Baide, Fátima P; Fernández Calvo, Miguel E

    2007-01-01

    Como parte de la implementación del sistema adversarial al proceso penal costarricense y la inminente eliminación del Consejo Médico Forense, se hace necesario que los psiquiatras y psicólogos forenses conozcan cuales son los nuevos retos a los que se enfrentaran al presentarse a debate y ser cuestionados, en cuanto a la realización de las pericias practicadas a personas menores de edad en delitos de Agresión Sexual. Es importante conocer el sistema de acreditación de peritos y las críticas m...

  10. La responsabilidad del Contador Público en empresas imputadas por delitos tipificados en la Ley Penal Tributaria

    OpenAIRE

    Rossana Greco; Oscar Nedel

    2013-01-01

    El objeto de estudio del presente trabajo es la responsabilidad del contador público en su actuación como auditor externo de estados contables, en el marco de la ley penal tributaria y previsional, teniendo en cuenta la modificación de la ley 24.769 introducida por la ley 26.735 (BO: 28.12.2011) que incorpora el concepto de responsabilidad empresarial, aceptando como sujeto no solo a la persona física, sino que también a la persona jurídica. La metodología utilizada se basó en la revisión doc...

  11. Accurate and versatile multivariable arbitrary piecewise model regression of nonlinear fluidic muscle behavior

    NARCIS (Netherlands)

    Veale, A.J.; Xie, Sheng Quan; Anderson, Iain Alexander

    2017-01-01

    Wearable exoskeletons and soft robots require actuators with muscle-like compliance. These actuators can benefit from the robust and effective interaction that biological muscles' compliance enables them to have in the uncertainty of the real world. Fluidic muscles are compliant but difficult to

  12. Multivariate Regression Model of Impedance of Normal and Chemically Irritated Skin Shows Predictive Ability

    National Research Council Canada - National Science Library

    Aberg, P

    2001-01-01

    ... before and after application of chemicals on volar forearms of volunteers, Tegobetaine and sodium lauryl sulphate were used to induce the irritations, The spectra were filtered using orthogonal signal correction (OSC...

  13. Factors Associated with Increased Pain in Primary Dysmenorrhea: Analysis Using a Multivariate Ordered Logistic Regression Model.

    Science.gov (United States)

    Tomás-Rodríguez, María I; Palazón-Bru, Antonio; Martínez-St John, Damian R J; Navarro-Cremades, Felipe; Toledo-Marhuenda, José V; Gil-Guillén, Vicente F

    2017-04-01

    In the literature about primary dysmenorrhea (PD), either a pain gradient has been studied just in women with PD or pain was assessed as a binary variable (presence or absence). Accordingly, we decided to carry out a study in young women to determine possible factors associated with intense pain. A cross-sectional observational study. A Spanish University in 2016. A total of 306 women, aged 18-30 years. A questionnaire was filled in by the participants to assess associated factors with dysmenorrhoea. Our outcome measure was the Andersch and Milsom scale (grade from 0 to 3). grade 0 (menstruation is not painful and daily activity is unaffected), grade 1 (menstruation is painful but seldom inhibits normal activity, analgesics are seldom required, and mild pain), grade 2 (daily activity affected, analgesics required and give relief so that absence from work or school is unusual, and moderate pain), and grade 3 (activity clearly inhibited, poor effect of analgesics, vegetative symptoms and severe pain). Factors significantly associated with more extreme pain: a higher menstrual flow (odds ratio [OR], 2.11; P < .001), a worse quality of life (OR, 0.97; P < .001) and use of medication for PD (OR, 8.22; P < .001). We determined factors associated with extreme pain in PD in a novel way. Further studies are required to corroborate our results. Copyright © 2016 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

  14. Differential diagnosis of degenerative dementias using basic neuropsychological tests: multivariable logistic regression analysis of 301 patients.

    Science.gov (United States)

    Jiménez-Huete, Adolfo; Riva, Elena; Toledano, Rafael; Campo, Pablo; Esteban, Jesús; Barrio, Antonio Del; Franch, Oriol

    2014-12-01

    The validity of neuropsychological tests for the differential diagnosis of degenerative dementias may depend on the clinical context. We constructed a series of logistic models taking into account this factor. We retrospectively analyzed the demographic and neuropsychological data of 301 patients with probable Alzheimer's disease (AD), frontotemporal degeneration (FTLD), or dementia with Lewy bodies (DLB). Nine models were constructed taking into account the diagnostic question (eg, AD vs DLB) and subpopulation (incident vs prevalent). The AD versus DLB model for all patients, including memory recovery and phonological fluency, was highly accurate (area under the curve = 0.919, sensitivity = 90%, and specificity = 80%). The results were comparable in incident and prevalent cases. The FTLD versus AD and DLB versus FTLD models were both inaccurate. The models constructed from basic neuropsychological variables allowed an accurate differential diagnosis of AD versus DLB but not of FTLD versus AD or DLB. © The Author(s) 2014.

  15. Deconvolution of Defocused Image with Multivariate Local Polynomial Regression and Iterative Wiener Filtering in DWT Domain

    Directory of Open Access Journals (Sweden)

    Liyun Su

    2010-01-01

    obtaining the point spread function (PSF parameter, iterative wiener filter is adopted to complete the restoration. We experimentally illustrate its performance on simulated data and real blurred image. Results show that the proposed PSF parameter estimation technique and the image restoration method are effective.

  16. Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

    Science.gov (United States)

    Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

    2017-08-01

    Objective. Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking. Approach. We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing. Main results. Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators. Significance. Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically-observable EEG data, with a variety of straightforward computation methods available. This opens possibilities for systematic assessments of ictal discharge propagation in clinical and research settings.

  17. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

    This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...

  18. Repensando la libertad de expresión desde el abordaje al art. 213 del Código Penal argentino

    Directory of Open Access Journals (Sweden)

    Matalone, Noelia

    2013-12-01

    Full Text Available Este ensayo intenta presentar abordajes críticos sobre el delito tipificado en el art. 213 del Código Penal. En tal temperamento, se contrapone el tipo penal de apología del delito con los derechos individuales de las personas, en particular, la libertad de expresión. En este sentido, la autora formula una propuesta de derogación de la norma, como consecuencia de los fundamentos y efectos de esta norma, todo ello en orden a preservar, por sobre los intereses que puedan sostener este tipo de prohibición, la pluralidad de voces en la sociedad. Para ello, apela al sentido de la tolerancia social y a los principios de razonalibidad y de necesidad del sistema penal al momento de investigar y perseguir este tipo de casos.

  19. Aporía de la política criminal del exhibicionismo penal en México

    Directory of Open Access Journals (Sweden)

    Alan Jair García Flores

    2017-01-01

    Full Text Available El presente artículo tiene como fin ulterior, esgrimir las líneas esenciales de la política criminal de exhibicionismo penal contra los presuntos responsables de la comisión de delitos, circunstancia que vulnera el esquema garantista del sistema penal mexicano adoptado a través de la reforma constitucional de 2008 y degrada el constructo social del Estado Democrático de Derecho , robustecido mediante la reforma constitucional en materia de derechos humanos de 2011. A lo larg o de los siguientes apartados, se esgrime un estudio sobre los derechos fundamentales lesionados por la práctica estatal del exhibicionismo penal, hecho que ha significado violaciones tanto al debido proceso legal como a la dignidad y honor de los gobernad os quienes deberían ser los principales sujetos de protección del Estado mexicano.

  20. Elliptical multiple-output quantile regression and convex optimization

    Czech Academy of Sciences Publication Activity Database

    Hallin, M.; Šiman, Miroslav

    2016-01-01

    Roč. 109, č. 1 (2016), s. 232-237 ISSN 0167-7152 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : quantile regression * elliptical quantile * multivariate quantile * multiple-output regression Subject RIV: BA - General Mathematics Impact factor: 0.540, year: 2016 http://library.utia.cas.cz/separaty/2016/SI/siman-0458243.pdf

  1. Multivariate calibration applied to the quantitative analysis of infrared spectra

    Energy Technology Data Exchange (ETDEWEB)

    Haaland, D.M.

    1991-01-01

    Multivariate calibration methods are very useful for improving the precision, accuracy, and reliability of quantitative spectral analyses. Spectroscopists can more effectively use these sophisticated statistical tools if they have a qualitative understanding of the techniques involved. A qualitative picture of the factor analysis multivariate calibration methods of partial least squares (PLS) and principal component regression (PCR) is presented using infrared calibrations based upon spectra of phosphosilicate glass thin films on silicon wafers. Comparisons of the relative prediction abilities of four different multivariate calibration methods are given based on Monte Carlo simulations of spectral calibration and prediction data. The success of multivariate spectral calibrations is demonstrated for several quantitative infrared studies. The infrared absorption and emission spectra of thin-film dielectrics used in the manufacture of microelectronic devices demonstrate rapid, nondestructive at-line and in-situ analyses using PLS calibrations. Finally, the application of multivariate spectral calibrations to reagentless analysis of blood is presented. We have found that the determination of glucose in whole blood taken from diabetics can be precisely monitored from the PLS calibration of either mind- or near-infrared spectra of the blood. Progress toward the non-invasive determination of glucose levels in diabetics is an ultimate goal of this research. 13 refs., 4 figs.

  2. Tratamiento de la delincuencia organizada en España: en particular, tras la reforma penal del 2010

    Directory of Open Access Journals (Sweden)

    José Luis De la Cuesta Arzamendi

    2013-04-01

    Full Text Available La reforma operada por la Ley Orgánica 5/2010 en el Código Penal español ha supuesto, en relación con la delincuencia organizada, una completa reestructuración de los tipos penales relativos a las organizaciones y grupos criminales, con lo que se supera la insatisfactoria situación anterior de ausencia de un concepto penal de organización criminal, que aparece ya legalmente establecido. No pocos son los problemas técnicos que suscita la nueva regulación, tanto en lo que se refiere a la extensión de los tipos penales como por el solapamiento de estos con otras modalidades delictivas y actos punibles (v. gr., los delitos de asociación ilícita, que continúan vigentes. Los defectos de técnica legislativa se extienden, igualmente, al campo de las sanciones y demás consecuencias jurídicas del delito, respecto de las que se confirma la tendencia endurecedora del ordenamiento jurídico español, el cual también se caracteriza por la progresiva introducción de regulaciones procesales específicas, dirigidas a favorecer la persecución penal. La presente contribución pasa revista a esta nueva situación normativa, que se analiza en la línea de la dogmática jurídico-penal, al poner de relieve sus contradicciones e insuficiencias desde el prisma políticocriminal en un área de la mayor importancia criminológica y para la seguridad de los ciudadanos.

  3. Multivariate methods for particle identification

    CERN Document Server

    Visan, Cosmin

    2013-01-01

    The purpose of this project was to evaluate several MultiVariate methods in order to determine which one, if any, offers better results in Particle Identification (PID) than a simple n$\\sigma$ cut on the response of the ALICE PID detectors. The particles considered in the analysis were Pions, Kaons and Protons and the detectors used were TPC and TOF. When used with the same input n$\\sigma$ variables, the results show similar perfoance between the Rectangular Cuts Optimization method and the simple n$\\sigma$ cuts. The method MLP and BDT show poor results for certain ranges of momentum. The KNN method is the best performing, showing similar results for Pions and Protons as the Cuts method, and better results for Kaons. The extension of the methods to include additional input variables leads to poor results, related to instabilities still to be investigated.

  4. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P E [Vestfold College, Maritime Dept., Toensberg (Norway)

    1998-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  5. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P.E. [Vestfold College, Maritime Dept., Toensberg (Norway)

    1997-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  6. Multivariate supOU processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Stelzer, Robert

    Univariate superpositions of Ornstein-Uhlenbeck (OU) type processes, called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behaviour. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness...... of moments. Moreover, the second order moment structure is explicitly calculated, and examples exhibit the possibility of long range dependence. Our supOU processes are defined via homogeneous and factorisable Lévy bases. We show that the behaviour of supOU processes is particularly nice when the mean...... reversion parameter is restricted to normal matrices and especially to strictly negative definite ones.For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation...

  7. Multivariate supOU processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Stelzer, Robert

    2011-01-01

    Univariate superpositions of Ornstein–Uhlenbeck-type processes (OU), called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behavior. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness of moments....... Moreover, the second-order moment structure is explicitly calculated, and examples exhibit the possibility of long-range dependence. Our supOU processes are defined via homogeneous and factorizable Lévy bases. We show that the behavior of supOU processes is particularly nice when the mean reversion...... parameter is restricted to normal matrices and especially to strictly negative definite ones. For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation of OU...

  8. An Exact Confidence Region in Multivariate Calibration

    OpenAIRE

    Mathew, Thomas; Kasala, Subramanyam

    1994-01-01

    In the multivariate calibration problem using a multivariate linear model, an exact confidence region is constructed. It is shown that the region is always nonempty and is invariant under nonsingular transformations.

  9. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  10. A Penalized Semialgebraic Deflation ICA Algorithm for the Efficient Extraction of Interictal Epileptic Signals.

    Science.gov (United States)

    Becker, Hanna; Albera, Laurent; Comon, Pierre; Kachenoura, Amar; Merlet, Isabelle

    2017-01-01

    As a noninvasive technique, electroencephalography (EEG) is commonly used to monitor the brain signals of patients with epilepsy such as the interictal epileptic spikes. However, the recorded data are often corrupted by artifacts originating, for example, from muscle activities, which may have much higher amplitudes than the interictal epileptic signals of interest. To remove these artifacts, a number of independent component analysis (ICA) techniques were successfully applied. In this paper, we propose a new deflation ICA algorithm, called penalized semialgebraic unitary deflation (P-SAUD) algorithm, that improves upon classical ICA methods by leading to a considerably reduced computational complexity at equivalent performance. This is achieved by employing a penalized semialgebraic extraction scheme, which permits us to identify the epileptic components of interest (interictal spikes) first and obviates the need of extracting subsequent components. The proposed method is evaluated on physiologically plausible simulated EEG data and actual measurements of three patients. The results are compared to those of several popular ICA algorithms as well as second-order blind source separation methods, demonstrating that P-SAUD extracts the epileptic spikes with the same accuracy as the best ICA methods, but reduces the computational complexity by a factor of 10 for 32-channel recordings. This superior computational efficiency is of particular interest considering the increasing use of high-resolution EEG recordings, whose analysis requires algorithms with low computational cost.

  11. Sex offender punishment and the persistence of penal harm in the U.S.

    Science.gov (United States)

    Leon, Chrysanthi S

    2011-01-01

    The U.S. has dramatically revised its approach to punishment in the last several decades. In particular, people convicted of sex crimes have experienced a remarkable expansion in social control through a wide-range of post-conviction interventions. While this expansion may be largely explained by general punishment trends, there appear to be unique factors that have prevented other penal reforms from similarly modulating sex offender punishment. In part, this continuation of a "penal harm" approach to sex offenders relates to the past under-valuing of sexual victimization. In the "bad old days," the law and its agents sent mixed messages about sexual violence and sexual offending. Some sexual offending was mere nuisance, some was treatable, and a fraction "deserved" punishment equivalent to other serious criminal offending. In contrast, today's sex offender punishment schemes rarely distinguish formally among gradations of harm or dangerousness. After examining incarceration trends, this article explores the historical context of the current broad brush approach and reviews the unintended consequences. Altogether, this article reinforces the need to return to differentiation among sex offenders, but differentiation based on science and on the experience-based, guided discretion of experts in law enforcement, corrections, and treatment. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Sistema penal acusatorio en Veracruz/Adversarial criminal system in Veracruz

    Directory of Open Access Journals (Sweden)

    Jorge Alberto Pérez Tolentino (México

    2014-01-01

    Full Text Available El estudio y comprensión del nuevo Código de Procedimientos Penales de Veracruz resulta ineludible, en virtud de las nítidas diferencias existentes entre las figuras jurídicas que contiene el actual ordenamiento, en comparación con el anterior. Es preciso sistematizar, describir y analizar la estructura del sistema penal acusatorio, a efecto de estar en condiciones de evaluar y, en su caso, proponer las mejoras al sistema en cuestión. El contenido esquemático y sustancial del código, la visión y recepción que del mismo tienen los operadores jurídicos y la sociedad en general, son aspectos que cubre el presente documento. The study and understanding of the new Code of Criminal Procedure of Veracruz is unavoidable, by reason of the sharp differences between the legal concepts that contains the actual order, compared with the previous. Needs to be systematized, describe and analyze the structure of the adversarial criminal system, in order to be able to evaluate and, if necessary, propose improvements to the system in question. The schematic and substantial content of the code, viewing and welcome that the same have the legal practitioners and society in general, are aspects covered by herein.

  13. PIRPLE: a penalized-likelihood framework for incorporation of prior images in CT reconstruction

    International Nuclear Information System (INIS)

    Stayman, J Webster; Dang, Hao; Ding, Yifu; Siewerdsen, Jeffrey H

    2013-01-01

    Over the course of diagnosis and treatment, it is common for a number of imaging studies to be acquired. Such imaging sequences can provide substantial patient-specific prior knowledge about the anatomy that can be incorporated into a prior-image-based tomographic reconstruction for improved image quality and better dose utilization. We present a general methodology using a model-based reconstruction approach including formulations of the measurement noise that also integrates prior images. This penalized-likelihood technique adopts a sparsity enforcing penalty that incorporates prior information yet allows for change between the current reconstruction and the prior image. Moreover, since prior images are generally not registered with the current image volume, we present a modified model-based approach that seeks a joint registration of the prior image in addition to the reconstruction of projection data. We demonstrate that the combined prior-image- and model-based technique outperforms methods that ignore the prior data or lack a noise model. Moreover, we demonstrate the importance of registration for prior-image-based reconstruction methods and show that the prior-image-registered penalized-likelihood estimation (PIRPLE) approach can maintain a high level of image quality in the presence of noisy and undersampled projection data. (paper)

  14. Penalized Nonlinear Least Squares Estimation of Time-Varying Parameters in Ordinary Differential Equations

    KAUST Repository

    Cao, Jiguo; Huang, Jianhua Z.; Wu, Hulin

    2012-01-01

    Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.

  15. Differentiation of penal policy in the light of positive paradigm and its confronting challenges

    Directory of Open Access Journals (Sweden)

    Bagher Shamlou

    2015-05-01

    Full Text Available Positivism is an empirical approach for understanding of human communication and phenomena, which raised firstly French famous thinker “August Comte”. Human and social Sciences were under domination of positive thought for a long time. In criminal law inter alia Italian famous thinkers sought to analyses the crime problem with a positive approach. However, some of their point of view such as born criminal thesis was not respected by penal scientist, but was affected by their idea was assumed that experiment is the only scientific criterion and basis of criminal law. They thought that value judgments and normative sentences have not scientific character. The positivist approach, developed the abstract thought of classic criminal fundamentalism which was before this, the dominate approach of penal policy towards of objectivism at etiology of crime on the basis of separation of objectivism and subjectivism. But it faced with insufficiency in both methodology and efficiency, so that somebody talked about returning punity approach of classic fundamentalism

  16. La función de la costumbre en el Estatuto de la Corte Penal Internacional

    Directory of Open Access Journals (Sweden)

    Noelia Trinidad Núñez

    2016-03-01

    Full Text Available Este trabajo se ocupa de la función de la costumbre como fundamento de la punibilidad en el Estatuto de la Corte Penal Internacional (ECPI. En primer lugar, estudia su lugar en el sistema de fuentes del Estatuto. Luego, investiga específicamente si en el ECPI existe una prohibición de fundamentar la punibilidad en el derecho consuetudinario. Para ello, estudia el alcance del principio de legalidad en el sistema de la CPI y su relación con el derecho consuetudinario. A continuación, analiza si el ECPI admite el recurso al derecho consuetudinario como criterio de interpretación, incluso en perjuicio del imputado. Finalmente, se ocupa de la propuesta de fundamentar la punibilidad directamente en normas consuetudinarias cuando la CPI ejerce jurisdicción sobre crímenes cometidos en el territorio y por nacionales de Estados no parte. El trabajo concluye que aunque el ECPI reconoce a la costumbre una función más marginal que la que tuvo en las experiencias precedentes de derecho internacional penal, existen, sin embargo, ámbitos en los que esta fuente puede tener significado y ello incluso en relación con la fundamentación de la punibilidad.

  17. La expectativa razonable de intimidad y el derecho fundamental a la intimidad en el proceso penal

    Directory of Open Access Journals (Sweden)

    Oscar Julián Guerrero Peralta

    2011-07-01

    Full Text Available El texto tiene el objetivo de ilustrar históricamente la formación de la categoría “expectativa razonable de intimidad” en el derecho procesal penal norteamericano y observar las dificultades de su adaptación a los sistemas continentales que cuentan con la intimidad como un derecho fundamental constitucional. En tal sentido, el artículo muestra la evolución de las discusiones jurisprudenciales de Norteamérica, empezando por la decisión Katz de los años 60’s hasta las modernas interpretaciones que extienden el modelo a la vigilancia aérea de objetos y personas. Frente a la legislación colombiana resulta importante destacar que la noción tiene otras perspectivas interesantes, que inscriben la problemática en una nueva realidad del derecho probatorio que se relaciona con la tecnología del control aplicada a las pruebas penales.

  18. Modelo Operativo de gestión de redes sociales para el sistema penal adolescente, Chile

    Directory of Open Access Journals (Sweden)

    Claudio Andradre-Gyllen

    2016-03-01

    Full Text Available En el artículo analizamos los principales resultados del diseño, implementación y evaluación de un modelo operativo de gestión de redes sociales, utilizando la metodología de investigación acción participante (IAP en programas del sistema de responsabilidad penal adolescente, en la Región de Los Ríos, Chile. Los resultados evidencian cambios favorables en la gestión y en la estructura de la red de actores de los programas participantes. El modelo operativo de gestión de redes sociales nos permitió superar las actuales restricciones de articulación del sistema de responsabilidad penal adolescente, dando énfasis a la capacidad de los actores del sistema para desarrollar nuevas formas de coordinación territorial que favorezcan la integración social de los individuos jóvenes infractores de ley.

  19. Construcciones sociales sobre mujeres desde el discurso jurídico en sentencias penales sobre infanticidio

    Directory of Open Access Journals (Sweden)

    María Eugenia Gastiazoro

    2015-12-01

    Full Text Available El infanticidio como figura penal se suprime del Código Penal Argentino en 1994, para ser una figura de homicidio agravado por el vínculo con prisión o reclusión perpetua. Diez años después de su última derogación, el caso Romina Tejerina en Jujuy generó una serie de cuestionamientos respecto de su penalización. Otro caso, que tomó estado público fue el de Eli Díaz en la ciudad de Villa Dolores en Córdoba, juzgada en el 2006, siendo (en contraposición al caso Tejerina absuelta por una mayoría compuesta solo de ciudadanos comunes (jurados. En el presente trabajo se analiza la construcción y la producción que desde el discurso jurídico se hace de las diferentes mujeres en los casos de infanticidio. A su vez, estas imágenes se comparan con las representaciones que los legisladores tuvieron en el debate del Congreso del año 2010 cuando se intentó reponer la figura. La sujeción del género centrada en la buena o mala madre, mujer, esposa, en intersección con otras dimensiones de clase social, y edad, se categoriza en el discurso de los tribunales de acuerdo a imaginarios sociales que sostienen una identidad normativa sobre estas mujeres.

  20. Improving multisensor estimation of heavy-to-extreme precipitation via conditional bias-penalized optimal estimation

    Science.gov (United States)

    Kim, Beomgeun; Seo, Dong-Jun; Noh, Seong Jin; Prat, Olivier P.; Nelson, Brian R.

    2018-01-01

    A new technique for merging radar precipitation estimates and rain gauge data is developed and evaluated to improve multisensor quantitative precipitation estimation (QPE), in particular, of heavy-to-extreme precipitation. Unlike the conventional cokriging methods which are susceptible to conditional bias (CB), the proposed technique, referred to herein as conditional bias-penalized cokriging (CBPCK), explicitly minimizes Type-II CB for improved quantitative estimation of heavy-to-extreme precipitation. CBPCK is a bivariate version of extended conditional bias-penalized kriging (ECBPK) developed for gauge-only analysis. To evaluate CBPCK, cross validation and visual examination are carried out using multi-year hourly radar and gauge data in the North Central Texas region in which CBPCK is compared with the variant of the ordinary cokriging (OCK) algorithm used operationally in the National Weather Service Multisensor Precipitation Estimator. The results show that CBPCK significantly reduces Type-II CB for estimation of heavy-to-extreme precipitation, and that the margin of improvement over OCK is larger in areas of higher fractional coverage (FC) of precipitation. When FC > 0.9 and hourly gauge precipitation is > 60 mm, the reduction in root mean squared error (RMSE) by CBPCK over radar-only (RO) is about 12 mm while the reduction in RMSE by OCK over RO is about 7 mm. CBPCK may be used in real-time analysis or in reanalysis of multisensor precipitation for which accurate estimation of heavy-to-extreme precipitation is of particular importance.