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Sample records for generalized linear mixed

  1. Generalized, Linear, and Mixed Models

    CERN Document Server

    McCulloch, Charles E; Neuhaus, John M

    2011-01-01

    An accessible and self-contained introduction to statistical models-now in a modernized new editionGeneralized, Linear, and Mixed Models, Second Edition provides an up-to-date treatment of the essential techniques for developing and applying a wide variety of statistical models. The book presents thorough and unified coverage of the theory behind generalized, linear, and mixed models and highlights their similarities and differences in various construction, application, and computational aspects.A clear introduction to the basic ideas of fixed effects models, random effects models, and mixed m

  2. Multivariate generalized linear mixed models using R

    CERN Document Server

    Berridge, Damon Mark

    2011-01-01

    Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound models for analyzing large and complex data sets, enabling readers to answer increasingly complex research questions. The book applies the principles of modeling to longitudinal data from panel and related studies via the Sabre software package in R. A Unified Framework for a Broad Class of Models The authors first discuss members of the family of generalized linear models, gradually adding complexity to the modeling framework by incorporating random effects. After reviewing the generalized linear model notation, they illustrate a range of random effects models, including three-level, multivariate, endpoint, event history, and state dependence models. They estimate the multivariate generalized linear mixed models (MGLMMs) using either standard or adaptive Gaussian quadrature. The authors also compare two-level fixed and random effects linear models. The appendices contain additional information on quadrature, model...

  3. Multivariate Generalized Linear Mixed Models Using R

    CERN Document Server

    Berridge, Damon M

    2011-01-01

    To provide researchers with the ability to analyze large and complex data sets using robust models, this book presents a unified framework for a broad class of models that can be applied using a dedicated R package (Sabre). The first five chapters cover the analysis of multilevel models using univariate generalized linear mixed models (GLMMs). The next few chapters extend to multivariate GLMMs and the last chapters address more specialized topics, such as parallel computing for large-scale analyses. Each chapter includes many real-world examples implemented using Sabre as well as exercises and

  4. A Note on the Identifiability of Generalized Linear Mixed Models

    DEFF Research Database (Denmark)

    Labouriau, Rodrigo

    2014-01-01

    I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity ...... conditions, and, therefore, is extensible to quasi-likelihood based generalized linear models. In particular, binomial and Poisson mixed models with dispersion parameter are identifiable when equipped with the standard parametrization......I present here a simple proof that, under general regularity conditions, the standard parametrization of generalized linear mixed model is identifiable. The proof is based on the assumptions of generalized linear mixed models on the first and second order moments and some general mild regularity...

  5. Practical likelihood analysis for spatial generalized linear mixed models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Ribeiro, Paulo Justiniano

    2016-01-01

    We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are, respectiv......We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...

  6. Mixed Task and Data Parallel Executions in General Linear Methods

    Directory of Open Access Journals (Sweden)

    Thomas Rauber

    2007-01-01

    Full Text Available On many parallel target platforms it can be advantageous to implement parallel applications as a collection of multiprocessor tasks that are concurrently executed and are internally implemented with fine-grain SPMD parallelism. A class of applications which can benefit from this programming style are methods for solving systems of ordinary differential equations. Many recent solvers have been designed with an additional potential of method parallelism, but the actual effectiveness of mixed task and data parallelism depends on the specific communication and computation requirements imposed by the equation to be solved. In this paper we study mixed task and data parallel implementations for general linear methods realized using a library for multiprocessor task programming. Experiments on a number of different platforms show good efficiency results.

  7. Extending the linear model with R generalized linear, mixed effects and nonparametric regression models

    CERN Document Server

    Faraway, Julian J

    2005-01-01

    Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway''s critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those footsteps, Extending the Linear Model with R surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author''s treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. To demonstrate the interplay of theory and practice, throughout the book the author weaves the use of the R software environment to analyze the data of real examples, providing all of the R commands necessary to reproduce the analyses. All of the ...

  8. Conditional likelihood inference in generalized linear mixed models.

    OpenAIRE

    Sartori, Nicola; Severini , T.A

    2002-01-01

    Consider a generalized linear model with a canonical link function, containing both fixed and random effects. In this paper, we consider inference about the fixed effects based on a conditional likelihood function. It is shown that this conditional likelihood function is valid for any distribution of the random effects and, hence, the resulting inferences about the fixed effects are insensitive to misspecification of the random effects distribution. Inferences based on the conditional likelih...

  9. Assessing correlation of clustered mixed outcomes from a multivariate generalized linear mixed model.

    Science.gov (United States)

    Chen, Hsiang-Chun; Wehrly, Thomas E

    2015-02-20

    The classic concordance correlation coefficient measures the agreement between two variables. In recent studies, concordance correlation coefficients have been generalized to deal with responses from a distribution from the exponential family using the univariate generalized linear mixed model. Multivariate data arise when responses on the same unit are measured repeatedly by several methods. The relationship among these responses is often of interest. In clustered mixed data, the correlation could be present between repeated measurements either within the same observer or between different methods on the same subjects. Indices for measuring such association are needed. This study proposes a series of indices, namely, intra-correlation, inter-correlation, and total correlation coefficients to measure the correlation under various circumstances in a multivariate generalized linear model, especially for joint modeling of clustered count and continuous outcomes. The proposed indices are natural extensions of the concordance correlation coefficient. We demonstrate the methodology with simulation studies. A case example of osteoarthritis study is provided to illustrate the use of these proposed indices. Copyright © 2014 John Wiley & Sons, Ltd.

  10. Generalized linear longitudinal mixed models with linear covariance structure and multiplicative random effects

    DEFF Research Database (Denmark)

    Holst, René; Jørgensen, Bent

    2015-01-01

    The paper proposes a versatile class of multiplicative generalized linear longitudinal mixed models (GLLMM) with additive dispersion components, based on explicit modelling of the covariance structure. The class incorporates a longitudinal structure into the random effects models and retains...... a marginal as well as a conditional interpretation. The estimation procedure is based on a computationally efficient quasi-score method for the regression parameters combined with a REML-like bias-corrected Pearson estimating function for the dispersion and correlation parameters. This avoids...... the multidimensional integral of the conventional GLMM likelihood and allows an extension of the robust empirical sandwich estimator for use with both association and regression parameters. The method is applied to a set of otholit data, used for age determination of fish....

  11. Generalized linear mixed models modern concepts, methods and applications

    CERN Document Server

    Stroup, Walter W

    2012-01-01

    PART I The Big PictureModeling BasicsWhat Is a Model?Two Model Forms: Model Equation and Probability DistributionTypes of Model EffectsWriting Models in Matrix FormSummary: Essential Elements for a Complete Statement of the ModelDesign MattersIntroductory Ideas for Translating Design and Objectives into ModelsDescribing ""Data Architecture"" to Facilitate Model SpecificationFrom Plot Plan to Linear PredictorDistribution MattersMore Complex Example: Multiple Factors with Different Units of ReplicationSetting the StageGoals for Inference with Models: OverviewBasic Tools of InferenceIssue I: Data

  12. Bayesian generalized linear mixed modeling of Tuberculosis using informative priors.

    Science.gov (United States)

    Ojo, Oluwatobi Blessing; Lougue, Siaka; Woldegerima, Woldegebriel Assefa

    2017-01-01

    TB is rated as one of the world's deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014.

  13. Scheme for purifying a general mixed entangled state and its linear optical implementation

    Institute of Scientific and Technical Information of China (English)

    董冬; 张延磊; 邹长铃; 邹旭波; 郭光灿

    2015-01-01

    We propose a scheme for purification of a general mixed entangled state. In this scheme, we start from a large number of general mixed entangled states and end up, after local operation and classical communication, with a smaller number of Bell diagonal states with higher entanglement. In particular, the scheme can purify one maximally entangled state from two entangled pairs prepared in a class of mixed entangled state. Furthermore we propose a linear optical implementation of the present scheme with polarization beam splitters and photon detectors.

  14. Estimate of influenza cases using generalized linear, additive and mixed models.

    Science.gov (United States)

    Oviedo, Manuel; Domínguez, Ángela; Pilar Muñoz, M

    2015-01-01

    We investigated the relationship between reported cases of influenza in Catalonia (Spain). Covariates analyzed were: population, age, data of report of influenza, and health region during 2010-2014 using data obtained from the SISAP program (Institut Catala de la Salut - Generalitat of Catalonia). Reported cases were related with the study of covariates using a descriptive analysis. Generalized Linear Models, Generalized Additive Models and Generalized Additive Mixed Models were used to estimate the evolution of the transmission of influenza. Additive models can estimate non-linear effects of the covariates by smooth functions; and mixed models can estimate data dependence and variability in factor variables using correlations structures and random effects, respectively. The incidence rate of influenza was calculated as the incidence per 100 000 people. The mean rate was 13.75 (range 0-27.5) in the winter months (December, January, February) and 3.38 (range 0-12.57) in the remaining months. Statistical analysis showed that Generalized Additive Mixed Models were better adapted to the temporal evolution of influenza (serial correlation 0.59) than classical linear models.

  15. Bayesian prediction of spatial count data using generalized linear mixed models

    DEFF Research Database (Denmark)

    Christensen, Ole Fredslund; Waagepetersen, Rasmus Plenge

    2002-01-01

    Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, we...... demonstrate that so-called Langevin-Hastings updates are useful for efficient simulation of the posterior distributions, and we discuss computational issues concerning prediction....

  16. Spatial variability in floodplain sedimentation: the use of generalized linear mixed-effects models

    Directory of Open Access Journals (Sweden)

    A. Cabezas

    2010-02-01

    Full Text Available Sediment, Total Organic Carbon (TOC and total nitrogen (TN accumulation during one overbank flood (1.15 y were examined at one reach of the Middle Ebro River (NE Spain for elucidating spatial patterns. To achieve this goal, four areas with different geomorphological features and located within the study reach were examined by using artificial grass mats. Within each area, 1 m2 study plots consisting on three pseudo-replicates were placed in a semi-regular grid oriented perpendicular to the main channel. TOC, TN and Particle-Size composition of deposited sediments were examined and accumulation rates estimated. Generalized linear mixed-effects models were used to analyze sedimentation patterns in order to handle clustered sampling units, specific-site effects and spatial self-correlation between observations. Our results confirm the importance of channel-floodplain morphology and site micro-topography in explaining sediment, TOC and TN deposition patterns, although the importance of another factors as vegetation morphology should be included in further studies to explain small scale variability. Generalized linear mixed-effect models provide a good framework to deal with the high spatial heterogeneity of this phenomenon at different spatial scales, and should be further investigated in order to explore its validity when examining the importance of factors such as flood magnitude or suspended sediment solid concentration.

  17. Spatial variability in floodplain sedimentation: the use of generalized linear mixed-effects models

    Science.gov (United States)

    Cabezas, A.; Angulo-Martínez, M.; Gonzalez-Sanchís, M.; Jimenez, J. J.; Comín, F. A.

    2010-08-01

    Sediment, Total Organic Carbon (TOC) and total nitrogen (TN) accumulation during one overbank flood (1.15 y return interval) were examined at one reach of the Middle Ebro River (NE Spain) for elucidating spatial patterns. To achieve this goal, four areas with different geomorphological features and located within the study reach were examined by using artificial grass mats. Within each area, 1 m2 study plots consisting of three pseudo-replicates were placed in a semi-regular grid oriented perpendicular to the main channel. TOC, TN and Particle-Size composition of deposited sediments were examined and accumulation rates estimated. Generalized linear mixed-effects models were used to analyze sedimentation patterns in order to handle clustered sampling units, specific-site effects and spatial self-correlation between observations. Our results confirm the importance of channel-floodplain morphology and site micro-topography in explaining sediment, TOC and TN deposition patterns, although the importance of other factors as vegetation pattern should be included in further studies to explain small-scale variability. Generalized linear mixed-effect models provide a good framework to deal with the high spatial heterogeneity of this phenomenon at different spatial scales, and should be further investigated in order to explore its validity when examining the importance of factors such as flood magnitude or suspended sediment concentration.

  18. Generalized linear mixed models for multi-reader multi-case studies of diagnostic tests.

    Science.gov (United States)

    Liu, Wei; Pantoja-Galicia, Norberto; Zhang, Bo; Kotz, Richard M; Pennello, Gene; Zhang, Hui; Jacob, Jessie; Zhang, Zhiwei

    2017-06-01

    Diagnostic tests are often compared in multi-reader multi-case (MRMC) studies in which a number of cases (subjects with or without the disease in question) are examined by several readers using all tests to be compared. One of the commonly used methods for analyzing MRMC data is the Obuchowski-Rockette (OR) method, which assumes that the true area under the receiver operating characteristic curve (AUC) for each combination of reader and test follows a linear mixed model with fixed effects for test and random effects for reader and the reader-test interaction. This article proposes generalized linear mixed models which generalize the OR model by incorporating a range-appropriate link function that constrains the true AUCs to the unit interval. The proposed models can be estimated by maximizing a pseudo-likelihood based on the approximate normality of AUC estimates. A Monte Carlo expectation-maximization algorithm can be used to maximize the pseudo-likelihood, and a non-parametric bootstrap procedure can be used for inference. The proposed method is evaluated in a simulation study and applied to an MRMC study of breast cancer detection.

  19. A generalization of the MDS method by mixed integer linear and nonlinear mathematical models

    Directory of Open Access Journals (Sweden)

    Sadegh Niroomand

    2014-09-01

    Full Text Available The Multi-Dimensional Scaling (MDS method is used in statistics to detect hidden interrelations among multi-dimensional data and it has a wide range of applications. The method’s input is a matrix that describes the similarity/dissimilarity among objects of unknown dimension. The objects are generally reconstructed as points of a lower dimensional space to reveal the geometric configuration of the objects. The original MDS method uses Euclidean distance, for measuring both the distance of the reconstructed points and the bias of the reconstructed distances from the original similarity values. In this paper, these distances are distinguished, and distances other than Euclidean are also used, generalizing the MDS method. Two different distances may be used for the two different purposes. Therefore the instances of the generalized MDS model are denoted as  model, where the first distance is the type of distance of the reconstructed points and the second one measures the bias of the reconstructed distances and the similarity values. In the case of   and   distances mixed-integer programming models are provided. The computational experiences show that the generalized model can catch the key properties of the original configuration, if any exist. Keywords: Multivariate Analysis; Multi-Dimensional Scaling; Optimization; Mixed Integer Linear Programming; Statistics.

  20. A generalized concordance correlation coefficient based on the variance components generalized linear mixed models for overdispersed count data.

    Science.gov (United States)

    Carrasco, Josep L

    2010-09-01

    The classical concordance correlation coefficient (CCC) to measure agreement among a set of observers assumes data to be distributed as normal and a linear relationship between the mean and the subject and observer effects. Here, the CCC is generalized to afford any distribution from the exponential family by means of the generalized linear mixed models (GLMMs) theory and applied to the case of overdispersed count data. An example of CD34+ cell count data is provided to show the applicability of the procedure. In the latter case, different CCCs are defined and applied to the data by changing the GLMM that fits the data. A simulation study is carried out to explore the behavior of the procedure with a small and moderate sample size.

  1. Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models

    CERN Document Server

    Hughes, John

    2010-01-01

    Non-gaussian spatial data are very common in many disciplines. For instance, count data are common in disease mapping, and binary data are common in ecology. When fitting spatial regressions for such data, one needs to account for dependence to ensure reliable inference for the regression coefficients. The spatial generalized linear mixed model (SGLMM) offers a very popular and flexible approach to modeling such data, but the SGLMM suffers from three major shortcomings: (1) uninterpretability of parameters due to spatial confounding, (2) variance inflation due to spatial confounding, and (3) high-dimensional spatial random effects that make fully Bayesian inference for such models computationally challenging. We propose a new parameterization of the SGLMM that alleviates spatial confounding and speeds computation by greatly reducing the dimension of the spatial random effects. We illustrate the application of our approach to simulated binary, count, and Gaussian spatial datasets, and to a large infant mortali...

  2. MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package

    Directory of Open Access Journals (Sweden)

    Jarrod Had

    2010-02-01

    Full Text Available Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form. Markov chain Monte Carlo methods solve this problem by sampling from a series of simpler conditional distributions that can be evaluated. The R package MCMCglmm implements such an algorithm for a range of model fitting problems. More than one response variable can be analyzed simultaneously, and these variables are allowed to follow Gaussian, Poisson, multi(binominal, exponential, zero-inflated and censored distributions. A range of variance structures are permitted for the random effects, including interactions with categorical or continuous variables (i.e., random regression, and more complicated variance structures that arise through shared ancestry, either through a pedigree or through a phylogeny. Missing values are permitted in the response variable(s and data can be known up to some level of measurement error as in meta-analysis. All simu- lation is done in C/ C++ using the CSparse library for sparse linear systems.

  3. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus

    2006-01-01

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  4. A simulation-based goodness-of-fit test for random effects in generalized linear mixed models

    DEFF Research Database (Denmark)

    Waagepetersen, Rasmus Plenge

    The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is assessed using a conditional simulation of the random effects conditional on the observations. Provided that the specified joint model for random effects and observations is correct, the marginal...

  5. A Priori Error Estimates of Mixed Finite Element Methods for General Linear Hyperbolic Convex Optimal Control Problems

    Directory of Open Access Journals (Sweden)

    Zuliang Lu

    2014-01-01

    Full Text Available The aim of this work is to investigate the discretization of general linear hyperbolic convex optimal control problems by using the mixed finite element methods. The state and costate are approximated by the k order (k≥0 Raviart-Thomas mixed finite elements and the control is approximated by piecewise polynomials of order k. By applying the elliptic projection operators and Gronwall’s lemma, we derive a priori error estimates of optimal order for both the coupled state and the control approximation.

  6. An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies.

    Science.gov (United States)

    Wang, Lily; Jia, Peilin; Wolfinger, Russell D; Chen, Xi; Grayson, Britney L; Aune, Thomas M; Zhao, Zhongming

    2011-03-01

    In genome-wide association studies (GWAS) of complex diseases, genetic variants having real but weak associations often fail to be detected at the stringent genome-wide significance level. Pathway analysis, which tests disease association with combined association signals from a group of variants in the same pathway, has become increasingly popular. However, because of the complexities in genetic data and the large sample sizes in typical GWAS, pathway analysis remains to be challenging. We propose a new statistical model for pathway analysis of GWAS. This model includes a fixed effects component that models mean disease association for a group of genes, and a random effects component that models how each gene's association with disease varies about the gene group mean, thus belongs to the class of mixed effects models. The proposed model is computationally efficient and uses only summary statistics. In addition, it corrects for the presence of overlapping genes and linkage disequilibrium (LD). Via simulated and real GWAS data, we showed our model improved power over currently available pathway analysis methods while preserving type I error rate. Furthermore, using the WTCCC Type 1 Diabetes (T1D) dataset, we demonstrated mixed model analysis identified meaningful biological processes that agreed well with previous reports on T1D. Therefore, the proposed methodology provides an efficient statistical modeling framework for systems analysis of GWAS. The software code for mixed models analysis is freely available at http://biostat.mc.vanderbilt.edu/LilyWang.

  7. Methodological quality and reporting of generalized linear mixed models in clinical medicine (2000-2012: a systematic review.

    Directory of Open Access Journals (Sweden)

    Martí Casals

    Full Text Available BACKGROUND: Modeling count and binary data collected in hierarchical designs have increased the use of Generalized Linear Mixed Models (GLMMs in medicine. This article presents a systematic review of the application and quality of results and information reported from GLMMs in the field of clinical medicine. METHODS: A search using the Web of Science database was performed for published original articles in medical journals from 2000 to 2012. The search strategy included the topic "generalized linear mixed models","hierarchical generalized linear models", "multilevel generalized linear model" and as a research domain we refined by science technology. Papers reporting methodological considerations without application, and those that were not involved in clinical medicine or written in English were excluded. RESULTS: A total of 443 articles were detected, with an increase over time in the number of articles. In total, 108 articles fit the inclusion criteria. Of these, 54.6% were declared to be longitudinal studies, whereas 58.3% and 26.9% were defined as repeated measurements and multilevel design, respectively. Twenty-two articles belonged to environmental and occupational public health, 10 articles to clinical neurology, 8 to oncology, and 7 to infectious diseases and pediatrics. The distribution of the response variable was reported in 88% of the articles, predominantly Binomial (n = 64 or Poisson (n = 22. Most of the useful information about GLMMs was not reported in most cases. Variance estimates of random effects were described in only 8 articles (9.2%. The model validation, the method of covariate selection and the method of goodness of fit were only reported in 8.0%, 36.8% and 14.9% of the articles, respectively. CONCLUSIONS: During recent years, the use of GLMMs in medical literature has increased to take into account the correlation of data when modeling qualitative data or counts. According to the current recommendations, the

  8. Effect of Smoothing in Generalized Linear Mixed Models on the Estimation of Covariance Parameters for Longitudinal Data.

    Science.gov (United States)

    Mullah, Muhammad Abu Shadeque; Benedetti, Andrea

    2016-11-01

    Besides being mainly used for analyzing clustered or longitudinal data, generalized linear mixed models can also be used for smoothing via restricting changes in the fit at the knots in regression splines. The resulting models are usually called semiparametric mixed models (SPMMs). We investigate the effect of smoothing using SPMMs on the correlation and variance parameter estimates for serially correlated longitudinal normal, Poisson and binary data. Through simulations, we compare the performance of SPMMs to other simpler methods for estimating the nonlinear association such as fractional polynomials, and using a parametric nonlinear function. Simulation results suggest that, in general, the SPMMs recover the true curves very well and yield reasonable estimates of the correlation and variance parameters. However, for binary outcomes, SPMMs produce biased estimates of the variance parameters for high serially correlated data. We apply these methods to a dataset investigating the association between CD4 cell count and time since seroconversion for HIV infected men enrolled in the Multicenter AIDS Cohort Study.

  9. The statistical performance of an MCF-7 cell culture assay evaluated using generalized linear mixed models and a score test.

    Science.gov (United States)

    Rey deCastro, B; Neuberg, Donna

    2007-05-30

    Biological assays often utilize experimental designs where observations are replicated at multiple levels, and where each level represents a separate component of the assay's overall variance. Statistical analysis of such data usually ignores these design effects, whereas more sophisticated methods would improve the statistical power of assays. This report evaluates the statistical performance of an in vitro MCF-7 cell proliferation assay (E-SCREEN) by identifying the optimal generalized linear mixed model (GLMM) that accurately represents the assay's experimental design and variance components. Our statistical assessment found that 17beta-oestradiol cell culture assay data were best modelled with a GLMM configured with a reciprocal link function, a gamma error distribution, and three sources of design variation: plate-to-plate; well-to-well, and the interaction between plate-to-plate variation and dose. The gamma-distributed random error of the assay was estimated to have a coefficient of variation (COV) = 3.2 per cent, and a variance component score test described by X. Lin found that each of the three variance components were statistically significant. The optimal GLMM also confirmed the estrogenicity of five weakly oestrogenic polychlorinated biphenyls (PCBs 17, 49, 66, 74, and 128). Based on information criteria, the optimal gamma GLMM consistently out-performed equivalent naive normal and log-normal linear models, both with and without random effects terms. Because the gamma GLMM was by far the best model on conceptual and empirical grounds, and requires only trivially more effort to use, we encourage its use and suggest that naive models be avoided when possible. Copyright 2006 John Wiley & Sons, Ltd.

  10. A Community Needs Index for Adolescent Pregnancy Prevention Program Planning: Application of Spatial Generalized Linear Mixed Models.

    Science.gov (United States)

    Johnson, Glen D; Mesler, Kristine; Kacica, Marilyn A

    2017-02-06

    Objective The objective is to estimate community needs with respect to risky adolescent sexual behavior in a way that is risk-adjusted for multiple community factors. Methods Generalized linear mixed modeling was applied for estimating teen pregnancy and sexually transmitted disease (STD) incidence by postal ZIP code in New York State, in a way that adjusts for other community covariables and residual spatial autocorrelation. A community needs index was then obtained by summing the risk-adjusted estimates of pregnancy and STD cases. Results Poisson regression with a spatial random effect was chosen among competing modeling approaches. Both the risk-adjusted caseloads and rates were computed for ZIP codes, which allowed risk-based prioritization to help guide funding decisions for a comprehensive adolescent pregnancy prevention program. Conclusions This approach provides quantitative evidence of community needs with respect to risky adolescent sexual behavior, while adjusting for other community-level variables and stabilizing estimates in areas with small populations. Therefore, it was well accepted by the affected groups and proved valuable for program planning. This methodology may also prove valuable for follow up program evaluation. Current research is directed towards further improving the statistical modeling approach and applying to different health and behavioral outcomes, along with different predictor variables.

  11. SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models.

    Science.gov (United States)

    Vock, David M; Davidian, Marie; Tsiatis, Anastasios A

    2014-01-01

    Generalized linear and nonlinear mixed models (GMMMs and NLMMs) are commonly used to represent non-Gaussian or nonlinear longitudinal or clustered data. A common assumption is that the random effects are Gaussian. However, this assumption may be unrealistic in some applications, and misspecification of the random effects density may lead to maximum likelihood parameter estimators that are inconsistent, biased, and inefficient. Because testing if the random effects are Gaussian is difficult, previous research has recommended using a flexible random effects density. However, computational limitations have precluded widespread use of flexible random effects densities for GLMMs and NLMMs. We develop a SAS macro, SNP_NLMM, that overcomes the computational challenges to fit GLMMs and NLMMs where the random effects are assumed to follow a smooth density that can be represented by the seminonparametric formulation proposed by Gallant and Nychka (1987). The macro is flexible enough to allow for any density of the response conditional on the random effects and any nonlinear mean trajectory. We demonstrate the SNP_NLMM macro on a GLMM of the disease progression of toenail infection and on a NLMM of intravenous drug concentration over time.

  12. Nested generalized linear mixed model with ordinal response: Simulation and application on poverty data in Java Island

    Science.gov (United States)

    Widyaningsih, Yekti; Saefuddin, Asep; Notodiputro, Khairil A.; Wigena, Aji H.

    2012-05-01

    The objective of this research is to build a nested generalized linear mixed model using an ordinal response variable with some covariates. There are three main jobs in this paper, i.e. parameters estimation procedure, simulation, and implementation of the model for the real data. At the part of parameters estimation procedure, concepts of threshold, nested random effect, and computational algorithm are described. The simulations data are built for 3 conditions to know the effect of different parameter values of random effect distributions. The last job is the implementation of the model for the data about poverty in 9 districts of Java Island. The districts are Kuningan, Karawang, and Majalengka chose randomly in West Java; Temanggung, Boyolali, and Cilacap from Central Java; and Blitar, Ngawi, and Jember from East Java. The covariates in this model are province, number of bad nutrition cases, number of farmer families, and number of health personnel. In this modeling, all covariates are grouped as ordinal scale. Unit observation in this research is sub-district (kecamatan) nested in district, and districts (kabupaten) are nested in province. For the result of simulation, ARB (Absolute Relative Bias) and RRMSE (Relative Root of mean square errors) scale is used. They show that prov parameters have the highest bias, but more stable RRMSE in all conditions. The simulation design needs to be improved by adding other condition, such as higher correlation between covariates. Furthermore, as the result of the model implementation for the data, only number of farmer family and number of medical personnel have significant contributions to the level of poverty in Central Java and East Java province, and only district 2 (Karawang) of province 1 (West Java) has different random effect from the others. The source of the data is PODES (Potensi Desa) 2008 from BPS (Badan Pusat Statistik).

  13. Non-Linear Mixed Logit

    DEFF Research Database (Denmark)

    Andersen, Steffen; Harrison, Glenn W.; Hole, Arne Risa

    2012-01-01

    We develop an extension of the familiar linear mixed logit model to allow for the direct estimation of parametric non-linear functions defined over structural parameters. Classic applications include the estimation of coefficients of utility functions to characterize risk attitudes and discountin...

  14. Multivariate covariance generalized linear models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Jørgensen, Bent

    2016-01-01

    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...... 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...

  15. Bayesian inference for generalized linear mixed model based on the multivariate t distribution in population pharmacokinetic study.

    Directory of Open Access Journals (Sweden)

    Fang-Rong Yan

    Full Text Available This article provides a fully bayesian approach for modeling of single-dose and complete pharmacokinetic data in a population pharmacokinetic (PK model. To overcome the impact of outliers and the difficulty of computation, a generalized linear model is chosen with the hypothesis that the errors follow a multivariate Student t distribution which is a heavy-tailed distribution. The aim of this study is to investigate and implement the performance of the multivariate t distribution to analyze population pharmacokinetic data. Bayesian predictive inferences and the Metropolis-Hastings algorithm schemes are used to process the intractable posterior integration. The precision and accuracy of the proposed model are illustrated by the simulating data and a real example of theophylline data.

  16. Generalized Linear Covariance Analysis

    Science.gov (United States)

    Carpenter, James R.; Markley, F. Landis

    2014-01-01

    This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

  17. Foundations of linear and generalized linear models

    CERN Document Server

    Agresti, Alan

    2015-01-01

    A valuable overview of the most important ideas and results in statistical analysis Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linear statistical models. The book presents a broad, in-depth overview of the most commonly used statistical models by discussing the theory underlying the models, R software applications, and examples with crafted models to elucidate key ideas and promote practical model building. The book begins by illustrating the fundamentals of linear models,

  18. Linear mixed models in sensometrics

    DEFF Research Database (Denmark)

    Kuznetsova, Alexandra

    quality of decision making in Danish as well as international food companies and other companies using the same methods. The two open-source R packages lmerTest and SensMixed implement and support the methodological developments in the research papers as well as the ANOVA modelling part of the Consumer......Today’s companies and researchers gather large amounts of data of different kind. In consumer studies the objective is the collection of the data to better understand consumer acceptance of products. In such studies a number of persons (generally not trained) are selected in order to score products......, texture, sound - depending on the aim of a study. It is a common approach in both studies to consider persons coming from a larger population, which, from the statistical perspective, leads to the use of mixed effects models, where consumers/assessors enter as random effects (Lawless and Heymann, 1997...

  19. Improved testing inference in mixed linear models

    CERN Document Server

    Melo, Tatiane F N; Cribari-Neto, Francisco; 10.1016/j.csda.2008.12.007

    2011-01-01

    Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Oftentimes, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test and also to a test obtained from a modified profile likelihood function. Our results generalize those in Zucker et al. (Journal of the Royal Statistical Society B, 2000, 62, 827-838) by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report numerical evidence which shows that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presente...

  20. A comparative study of generalized linear mixed modelling and artificial neural network approach for the joint modelling of survival and incidence of Dengue patients in Sri Lanka

    Science.gov (United States)

    Hapugoda, J. C.; Sooriyarachchi, M. R.

    2017-09-01

    Survival time of patients with a disease and the incidence of that particular disease (count) is frequently observed in medical studies with the data of a clustered nature. In many cases, though, the survival times and the count can be correlated in a way that, diseases that occur rarely could have shorter survival times or vice versa. Due to this fact, joint modelling of these two variables will provide interesting and certainly improved results than modelling these separately. Authors have previously proposed a methodology using Generalized Linear Mixed Models (GLMM) by joining the Discrete Time Hazard model with the Poisson Regression model to jointly model survival and count model. As Aritificial Neural Network (ANN) has become a most powerful computational tool to model complex non-linear systems, it was proposed to develop a new joint model of survival and count of Dengue patients of Sri Lanka by using that approach. Thus, the objective of this study is to develop a model using ANN approach and compare the results with the previously developed GLMM model. As the response variables are continuous in nature, Generalized Regression Neural Network (GRNN) approach was adopted to model the data. To compare the model fit, measures such as root mean square error (RMSE), absolute mean error (AME) and correlation coefficient (R) were used. The measures indicate the GRNN model fits the data better than the GLMM model.

  1. Introduction to general and generalized linear models

    CERN Document Server

    Madsen, Henrik

    2010-01-01

    IntroductionExamples of types of data Motivating examples A first view on the modelsThe Likelihood PrincipleIntroduction Point estimation theory The likelihood function The score function The information matrix Alternative parameterizations of the likelihood The maximum likelihood estimate (MLE) Distribution of the ML estimator Generalized loss-function and deviance Quadratic approximation of the log-likelihood Likelihood ratio tests Successive testing in hypothesis chains Dealing with nuisance parameters General Linear ModelsIntroduction The multivariate normal distribution General linear mod

  2. Bayesian inference for generalized linear mixed models with predictors subject to detection limits: an approach that leverages information from auxiliary variables.

    Science.gov (United States)

    Yue, Yu Ryan; Wang, Xiao-Feng

    2016-05-10

    This paper is motivated from a retrospective study of the impact of vitamin D deficiency on the clinical outcomes for critically ill patients in multi-center critical care units. The primary predictors of interest, vitamin D2 and D3 levels, are censored at a known detection limit. Within the context of generalized linear mixed models, we investigate statistical methods to handle multiple censored predictors in the presence of auxiliary variables. A Bayesian joint modeling approach is proposed to fit the complex heterogeneous multi-center data, in which the data information is fully used to estimate parameters of interest. Efficient Monte Carlo Markov chain algorithms are specifically developed depending on the nature of the response. Simulation studies demonstrate the outperformance of the proposed Bayesian approach over other existing methods. An application to the data set from the vitamin D deficiency study is presented. Possible extensions of the method regarding the absence of auxiliary variables, semiparametric models, as well as the type of censoring are also discussed.

  3. Linear mixed models for longitudinal data

    CERN Document Server

    Molenberghs, Geert

    2000-01-01

    This paperback edition is a reprint of the 2000 edition. This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mixed models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. However, some other commerc...

  4. Statistical Tests for Mixed Linear Models

    CERN Document Server

    Khuri, André I; Sinha, Bimal K

    2011-01-01

    An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models a

  5. Extending the simple linear regression model to account for correlated responses: an introduction to generalized estimating equations and multi-level mixed modelling.

    Science.gov (United States)

    Burton, P; Gurrin, L; Sly, P

    1998-06-15

    Much of the research in epidemiology and clinical science is based upon longitudinal designs which involve repeated measurements of a variable of interest in each of a series of individuals. Such designs can be very powerful, both statistically and scientifically, because they enable one to study changes within individual subjects over time or under varied conditions. However, this power arises because the repeated measurements tend to be correlated with one another, and this must be taken into proper account at the time of analysis or misleading conclusions may result. Recent advances in statistical theory and in software development mean that studies based upon such designs can now be analysed more easily, in a valid yet flexible manner, using a variety of approaches which include the use of generalized estimating equations, and mixed models which incorporate random effects. This paper provides a particularly simple illustration of the use of these two approaches, taking as a practical example the analysis of a study which examined the response of portable peak expiratory flow meters to changes in true peak expiratory flow in 12 children with asthma. The paper takes the reader through the relevant practicalities of model fitting, interpretation and criticism and demonstrates that, in a simple case such as this, analyses based upon these model-based approaches produce reassuringly similar inferences to standard analyses based upon more conventional methods.

  6. Homology stability for the general linear group

    NARCIS (Netherlands)

    Maazen, Hendrik

    1979-01-01

    This thesis studies the homology stability problem for general linear groups over Euclidean rings and over subrings of the field of rational numbers. Affine linear groups, acting on affine space rather than linear space, are also considered. In order to get stability results one establishes that cer

  7. Homology stability for the general linear group

    NARCIS (Netherlands)

    Maazen, Hendrik

    1979-01-01

    This thesis studies the homology stability problem for general linear groups over Euclidean rings and over subrings of the field of rational numbers. Affine linear groups, acting on affine space rather than linear space, are also considered. In order to get stability results one establishes that

  8. Efficient estimation of moments in linear mixed models

    CERN Document Server

    Wu, Ping; Zhu, Li-Xing; 10.3150/10-BEJ330

    2012-01-01

    In the linear random effects model, when distributional assumptions such as normality of the error variables cannot be justified, moments may serve as alternatives to describe relevant distributions in neighborhoods of their means. Generally, estimators may be obtained as solutions of estimating equations. It turns out that there may be several equations, each of them leading to consistent estimators, in which case finding the efficient estimator becomes a crucial problem. In this paper, we systematically study estimation of moments of the errors and random effects in linear mixed models.

  9. ROBUST ESTIMATION IN PARTIAL LINEAR MIXED MODEL FOR LONGITUDINAL DATA

    Institute of Scientific and Technical Information of China (English)

    Qin Guoyou; Zhu Zhongyi

    2008-01-01

    In this article, robust generalized estimating equation for the analysis of par- tial linear mixed model for longitudinal data is used. The authors approximate the non- parametric function by a regression spline. Under some regular conditions, the asymptotic properties of the estimators are obtained. To avoid the computation of high-dimensional integral, a robust Monte Carlo Newton-Raphson algorithm is used. Some simulations are carried out to study the performance of the proposed robust estimators. In addition, the authors also study the robustness and the efficiency of the proposed estimators by simulation. Finally, two real longitudinal data sets are analyzed.

  10. Generalized Cross-Gramian for Linear Systems

    DEFF Research Database (Denmark)

    Shaker, Hamid Reza

    2012-01-01

    The cross-gramian is a well-known matrix with embedded controllability and observability information. The cross-gramian is related to the Hankel operator and the Hankel singular values of a linear square system and it has several interesting properties. These properties make the cross-gramian...... popular in several applications including model reduction, control configuration selection and sensitivity analysis. The ordinary cross-gramian which has been defined in the literature is the solution of a Sylvester equation. This Sylvester equation is not always solvable and therefore for some linear...... square symmetric systems, the ordinary cross-gramian does not exist. To cope with this problem, a new generalized cross-gramian is introduced in this paper. In contrast to the ordinary cross-gramian, the generalized cross-gramian can be easily obtained for general linear systems and therefore can be used...

  11. Using generalized linear (mixed) models in HCI

    NARCIS (Netherlands)

    Kaptein, M.C.; Robertson, J; Kaptein, M

    2016-01-01

    In HCI we often encounter dependent variables which are not (conditionally) normally distributed: we measure response-times, mouse-clicks, or the number of dialog steps it took a user to complete a task. Furthermore, we often encounter nested or grouped data; users are grouped within companies or in

  12. General linear dynamics - quantum, classical or hybrid

    CERN Document Server

    Elze, H-T; Vallone, F

    2011-01-01

    We describe our recent proposal of a path integral formulation of classical Hamiltonian dynamics. Which leads us here to a new attempt at hybrid dynamics, which concerns the direct coupling of classical and quantum mechanical degrees of freedom. This is of practical as well as of foundational interest and no fully satisfactory solution of this problem has been established to date. Related aspects will be observed in a general linear ensemble theory, which comprises classical and quantum dynamics in the form of Liouville and von Neumann equations, respectively, as special cases. Considering the simplest object characterized by a two-dimensional state-space, we illustrate how quantum mechanics is special in several respects among possible linear generalizations.

  13. GENERALIZED DERIVATIONS ON PARABOLIC SUBALGEBRAS OF GENERAL LINEAR LIE ALGEBRAS

    Institute of Scientific and Technical Information of China (English)

    陈正新

    2014-01-01

    Let P be a parabolic subalgebra of a general linear Lie algebra gl(n, F) over a field F, where n ≥ 3, F contains at least n different elements, and char(F) 6= 2. In this article, we prove that generalized derivations, quasiderivations, and product zero derivations of P coincide, and any generalized derivation of P is a sum of an inner derivation, a central quasiderivation, and a scalar multiplication map of P. We also show that any commuting automorphism of P is a central automorphism, and any commuting derivation of P is a central derivation.

  14. Discontinuous Mixed Covolume Methods for Linear Parabolic Integrodifferential Problems

    Directory of Open Access Journals (Sweden)

    Ailing Zhu

    2014-01-01

    Full Text Available The semidiscrete and fully discrete discontinuous mixed covolume schemes for the linear parabolic integrodifferential problems on triangular meshes are proposed. The error analysis of the semidiscrete and fully discrete discontinuous mixed covolume scheme is presented and the optimal order error estimate in discontinuous H(div and first-order error estimate in L2 are obtained with the lowest order Raviart-Thomas mixed element space.

  15. [General practice--linear thinking and complexity].

    Science.gov (United States)

    Stalder, H

    2006-09-27

    As physicians, we apply and teach linear thinking. This approach permits to dissect the patient's problem to the molecular level and has contributed enormously to the knowledge and progress of medicine. The linear approach is particularly useful in medical education, in quantitative research and helps to resolve simple problems. However, it risks to be rigid. Living beings (such as patients and physicians!) have to be considered as complex systems. A complex system cannot be dissected into its parts without losing its identity. It is dependent on its past and interactions with the outside are often followed by unpredictable reactions. The patient-centred approach in medicine permits the physician, a complex system himself, to integrate the patient's system and to adapt to his reality. It is particularly useful in general medicine.

  16. Using R In Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    Mihaela Covrig

    2015-09-01

    Full Text Available This paper aims to approach the estimation of generalized linear models (GLM on the basis of the glm routine package in R. Particularly, regression models will be analyzed for those cases in which the explained variable follows a Poisson or a Negative Binomial distribution. The paper will briefly present the GLM methodology for count data, while the practical part will revolve around estimating and comparing models in which the response variable shows the number of claims in a portfolio of automobile insurance policies.

  17. Linear mixed models a practical guide using statistical software

    CERN Document Server

    West, Brady T; Galecki, Andrzej T

    2006-01-01

    Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), Linear Mixed Models: A Practical Guide Using Statistical Software provides a basic introduction to primary concepts, notation, software implementation, model interpretation, and visualization of clustered and longitudinal data. This easy-to-navigate reference details the use of procedures for fitting LMMs in five popular statistical software packages: SAS, SPSS, Stata, R/S-plus, and HLM. The authors introduce basic theoretical concepts, present a heuristic approach to fitting LMMs based on bo

  18. Multivariate Generalized Linear Mixed Models with High Complexity / Modèles linéaires généralisés mixtes multivariés avec complexité élevée

    DEFF Research Database (Denmark)

    Labouriau, Rodrigo

    The theory of exponential dispersion models (EDM), for which Bent Jørgensen made substantial contributions, provides a flexible framework of models alternative to the classic Gaussian linear models (e.g. generalized linear models and additive models). I review some multivariate extensions of thos...... aux EDMs pour bien représenter et interpréter les questions biologiques d'intérêt. Bent Jørgensen prônait des idées similaires dans son travail depuis les années 1980....

  19. Learning oncogenetic networks by reducing to mixed integer linear programming.

    Science.gov (United States)

    Shahrabi Farahani, Hossein; Lagergren, Jens

    2013-01-01

    Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

  20. Linear mixing rule in screened binary ionic mixtures

    Science.gov (United States)

    Chabrier, G.; Ashcroft, N. W.

    1990-01-01

    The validity of the linear mixing rule is examined for the following two cases (1) when the response of the electron gas is taken into account in the effective ionic interaction and (2) when finite-temperature effects are included in the dielectric response of the electrons, i.e., when the ions interact with both temperature- and density-dependent screened Coulomb potentials. It is found that the linear mixing rule remains valid when the electron response is taken into account in the interionic potential at any density, even though the departure from linearity can reach a few percent for the asymmetric mixtures in the region of weak degeneracy for the electron gas. A physical explanation of this behavior is proposed which is based on a simple additional length scale.

  1. A general extension of tribimaximal mixing

    CERN Document Server

    Ahn, Y H; Oh, Sechul

    2011-01-01

    Harrison, Perkins and Scott have proposed simple charged lepton and neutrino mass matrices that lead to the tribimaximal mixing $U_{\\rm TBM}$. We consider in this work a general extension of the mass matrices so that the leptonic mixing matrix becomes $U_{\\rm PMNS}=V_L^{\\ell\\dagger}U_{\\rm TBM}W$, where $V_L^\\ell$ is a unitary matrix needed to diagonalize the charged lepton mass matrix and $W$ measures the deviation of the neutrino mixing matrix from the bimaximal form. Hence, corrections to $U_{\\rm TBM}$ arise from both charged lepton and neutrino sectors. Following our previous work to assume a Qin-Ma-like parametrization $V_{\\rm QM}$ for the charged lepton mixing matrix $V_L^\\ell$ in which the {\\it CP}-odd phase is approximately maximal, we study the phenomenological implications in two different scenarios: $V_L^\\ell=V_{\\rm QM}^\\dagger$ and $V_L^\\ell=V_{\\rm QM}$. We find that the latter is more preferable, though both scenarios are consistent with the data within $3\\sigma$ ranges. The predicted central valu...

  2. Generalized Quadratic Linearization of Machine Models

    OpenAIRE

    Parvathy Ayalur Krishnamoorthy; Kamaraj Vijayarajan; Devanathan Rajagopalan

    2011-01-01

    In the exact linearization of involutive nonlinear system models, the issue of singularity needs to be addressed in practical applications. The approximate linearization technique due to Krener, based on Taylor series expansion, apart from being applicable to noninvolutive systems, allows the singularity issue to be circumvented. But approximate linearization, while removing terms up to certain order, also introduces terms of higher order than those removed into the system. To overcome th...

  3. A new estimate of the parameters in linear mixed models

    Institute of Scientific and Technical Information of China (English)

    王松桂; 尹素菊

    2002-01-01

    In linear mixed models, there are two kinds of unknown parameters: one is the fixed effect, theother is the variance component. In this paper, new estimates of these parameters, called the spectral decom-position estimates, are proposed, Some important statistical properties of the new estimates are established,in particular the linearity of the estimates of the fixed effects with many statistical optimalities. A new methodis applied to two important models which are used in economics, finance, and mechanical fields. All estimatesobtained have good statistical and practical meaning.

  4. Mixed-Integer-Linear-Programming-Based Energy Management System for Hybrid PV-Wind-Battery Microgrids

    DEFF Research Database (Denmark)

    Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Graells, Moises

    2017-01-01

    -side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data...

  5. General practice--linear thinking and complexity

    National Research Council Canada - National Science Library

    Stalder, H

    2006-01-01

    As physicians, we apply and teach linear thinking. This approach permits to dissect the patient's problem to the molecular level and has contributed enormously to the knowledge and progress of medicine...

  6. Mixed strategy under generalized public goods games.

    Science.gov (United States)

    Zhang, Yanling; Wu, Te; Chen, Xiaojie; Xie, Guangming; Wang, Long

    2013-10-07

    The relationship between group's contribution and public goods produced often exhibits nonlinearity, which constitutes the generalized public goods game. Far less attention has been paid to how the mixed strategy evolves in such generalized games. Here, we study the effects of nonlinear production functions on the evolution of the mixed strategy in finite populations for the first time. When the group size and the population size are comparable, cooperation is doomed irrespective of the production function. Otherwise, nonlinear production functions may induce a convergent evolutionary stable strategy (CESS) or a repeller, but cannot yield the evolutionary branching. Moreover, we particularly consider three representative families of production functions, intriguingly which all display the hysteresis effect. For two families of production functions including concave and convex curves, a unique CESS or a unique repeller may occur even if the group size is two. Whereas for the third class encompassing symmetrically sigmoidal and inverse sigmoidal curves, the coexistence of a CESS and a repeller only occurs if group size is above two, and two saddle-node bifurcations appear. Our work includes some evidently different results by comparing with the evolution of continuous investment or binary strategy.

  7. Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling

    DEFF Research Database (Denmark)

    Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian

    2014-01-01

    differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... of selected units by 23%, while for a non-linear approach the increase can be higher than 39%. The results indicate a higher coherence between the two latter approaches, and that the MLP (mixed integer programming) optimisation is most appropriate from a viewpoint of accuracy and runtime. © 2014 Elsevier Ltd...

  8. A Mixed Generalized Multifractal Formalism For Vector Valued Measures

    OpenAIRE

    Mabrouk, Anouar Ben

    2012-01-01

    We introduce a mixed generalized multifractal formalism which extends the mixed multifractal formalism introduced by L. Olsen based on generalizations of the Hausdorff and packing measures. The validity of such a formalism is proved in some special cases.

  9. Construction of extended exponential general linear methods 524 ...

    African Journals Online (AJOL)

    Construction of extended exponential general linear methods 524 for solving semi-linear problems. ... Journal Home > Vol 13, No 2 (2014) > ... This paper introduces a new approach for constructing higher order of EEGLM which have become ...

  10. Penalized maximum likelihood estimation for generalized linear point processes

    OpenAIRE

    2010-01-01

    A generalized linear point process is specified in terms of an intensity that depends upon a linear predictor process through a fixed non-linear function. We present a framework where the linear predictor is parametrized by a Banach space and give results on Gateaux differentiability of the log-likelihood. Of particular interest is when the intensity is expressed in terms of a linear filter parametrized by a Sobolev space. Using that the Sobolev spaces are reproducing kernel Hilbert spaces we...

  11. Abstract Acceleration of General Linear Loops

    OpenAIRE

    2014-01-01

    International audience; We present abstract acceleration techniques for computing loop invariants for numerical programs with linear assignments and conditionals. Whereas abstract interpretation techniques typically over-approximate the set of reachable states iteratively, abstract acceleration captures the effect of the loop with a single, non-iterative transfer function applied to the initial states at the loop head. In contrast to previous acceleration techniques, our approach applies to a...

  12. Generalized Ultrametric Semilattices of Linear Signals

    Science.gov (United States)

    2014-01-23

    ultrametric semilattice with a totally ordered distance set is isomorphic to a space of that kind. It follows that the formal definition of...from the National Science Foundation (NSF awards \\#0720882 ( CSR -EHS: PRET), \\#0931843 (CPS: Large: ActionWebs), and \\#1035672 (CPS: Medium: Timing...distance set is isomorphic to a space of that kind. It follows that the formal definition of generalized ultrametric semilattices with totally ordered

  13. Linear mixed models a practical guide using statistical software

    CERN Document Server

    West, Brady T; Galecki, Andrzej T

    2014-01-01

    Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM.New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggest...

  14. QUADRATIC INVARIANTS AND SYMPLECTIC STRUCTURE OF GENERAL LINEAR METHODS

    Institute of Scientific and Technical Information of China (English)

    Ai-guo Xiao; Shou-fu Li; Min Yang

    2001-01-01

    In this paper, we present some invariants and conservation laws of general linear methods applied to differential equation systems. We show that the quadratic invariants and symplecticity of the systems can be extended to general linear methods by a tensor product, and show that general linear methods with the matrix M=0 inherit in an extended sense the quadratic invariants possessed by the differential equation systems being integrated and preserve in an extended sense the symplectic structure of the phase space in the integration of Hamiltonian systems. These unify and extend existing relevant results on Runge-Kutta methods, linear multistep methods and one-leg methods. Finally, as special cases of general linear methods, we examine multistep Runge-Kutta methods, one-leg methods and linear two-step methods in detail.

  15. Linear models for sound from supersonic reacting mixing layers

    Science.gov (United States)

    Chary, P. Shivakanth; Samanta, Arnab

    2016-12-01

    We perform a linearized reduced-order modeling of the aeroacoustic sound sources in supersonic reacting mixing layers to explore their sensitivities to some of the flow parameters in radiating sound. Specifically, we investigate the role of outer modes as the effective flow compressibility is raised, when some of these are expected to dominate over the traditional Kelvin-Helmholtz (K-H) -type central mode. Although the outer modes are known to be of lesser importance in the near-field mixing, how these radiate to the far-field is uncertain, on which we focus. On keeping the flow compressibility fixed, the outer modes are realized via biasing the respective mean densities of the fast (oxidizer) or slow (fuel) side. Here the mean flows are laminar solutions of two-dimensional compressible boundary layers with an imposed composite (turbulent) spreading rate, which we show to significantly alter the growth of instability waves by saturating them earlier, similar to in nonlinear calculations, achieved here via solving the linear parabolized stability equations. As the flow parameters are varied, instability of the slow modes is shown to be more sensitive to heat release, potentially exceeding equivalent central modes, as these modes yield relatively compact sound sources with lesser spreading of the mixing layer, when compared to the corresponding fast modes. In contrast, the radiated sound seems to be relatively unaffected when the mixture equivalence ratio is varied, except for a lean mixture which is shown to yield a pronounced effect on the slow mode radiation by reducing its modal growth.

  16. Optical linear response function with linear and diagonal quadratic electron-vibration coupling in mixed quantum-classical systems.

    Science.gov (United States)

    Toutounji, Mohamad

    2004-08-01

    Optical linear response function of linearly and quadratically coupled mixed quantum-classical condensed phase systems is derived. The linear response function is derived using Kapral's formalism of statistical mechanics in mixed quantum-classical systems. Our mixed quantum-classical linear dipole moment correlation function J(t) is compared with the full quantum J(t) [Y. J. Yan and S. Mukamel, J. Chem. Phys. 85, 5908 (1986)] in the high temperature limit. Model calculations and discussion of our results are presented. Various formulas of Franck-Condon factors for both linear and quadratic coupling are discussed. (c) 2004 American Institute of Physics.

  17. Generalization of mixed multiscale finite element methods with applications

    Energy Technology Data Exchange (ETDEWEB)

    Lee, C S [Texas A & M Univ., College Station, TX (United States)

    2016-08-01

    Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixed multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii

  18. Generalized Multicarrier CDMA: Unification and Linear Equalization

    Directory of Open Access Journals (Sweden)

    Wang Zhengdao

    2005-01-01

    Full Text Available Relying on block-symbol spreading and judicious design of user codes, this paper builds on the generalized multicarrier (GMC quasisynchronous CDMA system that is capable of multiuser interference (MUI elimination and intersymbol interference (ISI suppression with guaranteed symbol recovery, regardless of the wireless frequency-selective channels. GMC-CDMA affords an all-digital unifying framework, which encompasses single-carrier and several multicarrier (MC CDMA systems. Besides the unifying framework, it is shown that GMC-CDMA offers flexibility both in full load (maximum number of users allowed by the available bandwidth and in reduced load settings. A novel blind channel estimation algorithm is also derived. Analytical evaluation and simulations illustrate the superior error performance and flexibility of uncoded GMC-CDMA over competing MC-CDMA alternatives especially in the presence of uplink multipath channels.

  19. Statistical tests with accurate size and power for balanced linear mixed models.

    Science.gov (United States)

    Muller, Keith E; Edwards, Lloyd J; Simpson, Sean L; Taylor, Douglas J

    2007-08-30

    The convenience of linear mixed models for Gaussian data has led to their widespread use. Unfortunately, standard mixed model tests often have greatly inflated test size in small samples. Many applications with correlated outcomes in medical imaging and other fields have simple properties which do not require the generality of a mixed model. Alternately, stating the special cases as a general linear multivariate model allows analysing them with either the univariate or multivariate approach to repeated measures (UNIREP, MULTIREP). Even in small samples, an appropriate UNIREP or MULTIREP test always controls test size and has a good power approximation, in sharp contrast to mixed model tests. Hence, mixed model tests should never be used when one of the UNIREP tests (uncorrected, Huynh-Feldt, Geisser-Greenhouse, Box conservative) or MULTIREP tests (Wilks, Hotelling-Lawley, Roy's, Pillai-Bartlett) apply. Convenient methods give exact power for the uncorrected and Box conservative tests. Simulations demonstrate that new power approximations for all four UNIREP tests eliminate most inaccuracy in existing methods. In turn, free software implements the approximations to give a better choice of sample size. Two repeated measures power analyses illustrate the methods. The examples highlight the advantages of examining the entire response surface of power as a function of sample size, mean differences, and variability.

  20. Designing Networks: A Mixed-Integer Linear Optimization Approach

    CERN Document Server

    Gounaris, Chrysanthos E; Kevrekidis, Ioannis G; Floudas, Christodoulos A

    2015-01-01

    Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this paper, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present a number of useful modeling techniques and apply them to mathematically express and constrain network properties in the context of an optimization formulation. We then develop complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.

  1. Delta-tilde interpretation of standard linear mixed model results

    DEFF Research Database (Denmark)

    Brockhoff, Per Bruun; Amorim, Isabel de Sousa; Kuznetsova, Alexandra

    2016-01-01

    effects relative to the residual error and to choose the proper effect size measure. For multi-attribute bar plots of F-statistics this amounts, in balanced settings, to a simple transformation of the bar heights to get them transformed into depicting what can be seen as approximately the average pairwise...... for factors with differences in number of levels. For mixed models, where in general the relevant error terms for the fixed effects are not the pure residual error, it is suggested to base the d-prime-like interpretation on the residual error. The methods are illustrated on a multifactorial sensory profile...... inherently challenging effect size measure estimates in ANOVA settings....

  2. Generalized Linear Models with Applications in Engineering and the Sciences

    CERN Document Server

    Myers, Raymond H; Vining, G Geoffrey; Robinson, Timothy J

    2012-01-01

    Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities."-Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Ma

  3. Natural connections given by general linear and classical connections

    OpenAIRE

    Janyška, Josef

    2004-01-01

    We assume a vector bundle $p: E\\to M$ with a general linear connection $K$ and a classical linear connection $\\Lam$ on $M$. We prove that all classical linear connections on the total space $E$ naturally given by $(\\Lam, K)$ form a 15-parameter family. Further we prove that all connections on $J^1 E$ naturally given by $(\\Lam, K)$ form a 14-parameter family. Both families of connections are described geometrically.

  4. A New Method for Solving General Dual Fuzzy Linear Systems

    Directory of Open Access Journals (Sweden)

    M. Otadi

    2013-09-01

    Full Text Available . According to fuzzy arithmetic, general dual fuzzy linear system (GDFLS cannot be replaced by a fuzzy linear system (FLS. In this paper, we use new notation of fuzzy numbers and convert a GDFLS to two linear systems in crisp case, then we discuss complexity of the proposed method. Conditions for the existence of a unique fuzzy solution to n × n GDFLS are derived

  5. Testing Parametric versus Semiparametric Modelling in Generalized Linear Models

    NARCIS (Netherlands)

    Härdle, W.K.; Mammen, E.; Müller, M.D.

    1996-01-01

    We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known function, b is an unknown parameter vector, and m is an unknown function.The paper introduces a test statistic which allows to decide between a parametric and a semiparametric model: (i) m is linear, i.e. m(

  6. Minimal solution of general dual fuzzy linear systems

    Energy Technology Data Exchange (ETDEWEB)

    Abbasbandy, S. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of); Department of Mathematics, Faculty of Science, Imam Khomeini International University, Qazvin 34194-288 (Iran, Islamic Republic of)], E-mail: abbasbandy@yahoo.com; Otadi, M.; Mosleh, M. [Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran 14778 (Iran, Islamic Republic of); Department of Mathematics, Islamic Azad University, Firuozkooh Branch, Firuozkooh (Iran, Islamic Republic of)

    2008-08-15

    Fuzzy linear systems of equations, play a major role in several applications in various area such as engineering, physics and economics. In this paper, we investigate the existence of a minimal solution of general dual fuzzy linear equation systems. Two necessary and sufficient conditions for the minimal solution existence are given. Also, some examples in engineering and economic are considered.

  7. Neural Generalized Predictive Control of a non-linear Process

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...

  8. Linear generalized synchronization of continuous-time chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Lu Junguo E-mail: jglu@sjtu.edu.cn; Xi Yugeng

    2003-08-01

    This paper develops a general approach for constructing a response system to implement linear generalized synchronization (GS) with the drive continuous-time chaotic system. Some sufficient conditions of global asymptotic linear GS between the drive and response continuous-time chaotic systems are attained from rigorously modern control theory. Finally, we take Chua's circuit as an example for illustration and verification.

  9. A general and simple method for obtaining R2 from generalized linear mixed‐effects models

    National Research Council Canada - National Science Library

    Nakagawa, Shinichi; Schielzeth, Holger; O'Hara, Robert B

    2013-01-01

    The use of both linear and generalized linear mixed‐effects models ( LMM s and GLMM s) has become popular not only in social and medical sciences, but also in biological sciences, especially in the field of ecology and evolution...

  10. Penalized maximum likelihood estimation for generalized linear point processes

    DEFF Research Database (Denmark)

    Hansen, Niels Richard

    2010-01-01

    A generalized linear point process is specified in terms of an intensity that depends upon a linear predictor process through a fixed non-linear function. We present a framework where the linear predictor is parametrized by a Banach space and give results on Gateaux differentiability of the log-likelihood....... Of particular interest is when the intensity is expressed in terms of a linear filter parametrized by a Sobolev space. Using that the Sobolev spaces are reproducing kernel Hilbert spaces we derive results on the representation of the penalized maximum likelihood estimator in a special case and the gradient...... of the negative log-likelihood in general. The latter is used to develop a descent algorithm in the Sobolev space. We conclude the paper by extensions to multivariate and additive model specifications. The methods are implemented in the R-package ppstat....

  11. Noether's theory of generalized linear nonholonomic mechanical systems

    Institute of Scientific and Technical Information of China (English)

    Dong Wen-Shan; Huang Bao-Xin; Fang Jian-Hui

    2011-01-01

    By introducing the quasi-symmetry of the infinitesimal transformation of the transformation group Gr, the Noether's theorem and the Noether's inverse theorem for generalized linear nonholonomic mechanical systems are obtained in a generalized compound derivative space. An example is given to illustrate the application of the result.

  12. Controllability of Linear Systems on Generalized Heisenberg Groups

    OpenAIRE

    Dath, Mouhamadou; Jouan, Philippe

    2015-01-01

    This paper is devoted to the study of controllability of linear systems on generalized Heisenberg groups. Some general necessary controllability conditions and some sufficient ones are provided. We introduce the notion of decoupled systems, and more precise controllability criteria are stated for them.

  13. McDonald Generalized Linear Failure Rate Distribution

    Directory of Open Access Journals (Sweden)

    Ibrahim Elbatal

    2014-10-01

    Full Text Available We introduce in this paper a new six-parameters generalized version of the generalized linear failure rate (GLFR distribution which is called McDonald Generalized Linear failure rate (McGLFR distribution. The new distribution is quite flexible and can be used effectively in modeling survival data and reliability problems. It can have a constant, decreasing, increasing, and upside down bathtub-and bathtub shaped failure rate function depending on its parameters. It includes some well-known lifetime distributions as special sub-models. Some structural properties of the new distribution are studied. Moreover we discuss maximum likelihood estimation of the unknown parameters of the new model.

  14. General Linear Models: An Integrated Approach to Statistics

    Directory of Open Access Journals (Sweden)

    Andrew Faulkner

    2008-09-01

    Full Text Available Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM, in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance is simply a multiple correlation/regression analysis (MCRA. Generalizations to other cases, such as multivariate and nonlinear analysis, are also discussed. It can easily be shown that every popular linear analysis can be derived from understanding MCRA.

  15. Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

    Science.gov (United States)

    Shek, Daniel T L; Ma, Cecilia M S

    2011-01-05

    Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

  16. Invertible Linear Maps on the General Linear Lie Algebras Preserving Solvability

    Institute of Scientific and Technical Information of China (English)

    CHEN ZHENG-XIN; CHEN QIONG

    2012-01-01

    Let Mn be the algebra of all n × n complex matrices and gl(n,C) be the general linear Lie algebra,where n ≥ 2.An invertible linear map ?:gl(n,C) →gl(n,C) preserves solvability in both directions if both ? and ?-1 map every solvable Lie subalgebra of gl(n,C) to some solvable Lie subalgebra.In this paper we classify the invertible linear maps preserving solvability on gl(n,C) in both directions.As a sequence,such maps coincide with the invertible linear maps preserving commutativity on Mn in both directions.

  17. General Linear Models: An Integrated Approach to Statistics

    OpenAIRE

    Andrew Faulkner; Sylvain Chartier

    2008-01-01

    Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM), in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance) is simply a multiple correlation/regression analysis (MCRA). Generalizations to other cases, such as multiv...

  18. Analyzing longitudinal data with the linear mixed models procedure in SPSS.

    Science.gov (United States)

    West, Brady T

    2009-09-01

    Many applied researchers analyzing longitudinal data share a common misconception: that specialized statistical software is necessary to fit hierarchical linear models (also known as linear mixed models [LMMs], or multilevel models) to longitudinal data sets. Although several specialized statistical software programs of high quality are available that allow researchers to fit these models to longitudinal data sets (e.g., HLM), rapid advances in general purpose statistical software packages have recently enabled analysts to fit these same models when using preferred packages that also enable other more common analyses. One of these general purpose statistical packages is SPSS, which includes a very flexible and powerful procedure for fitting LMMs to longitudinal data sets with continuous outcomes. This article aims to present readers with a practical discussion of how to analyze longitudinal data using the LMMs procedure in the SPSS statistical software package.

  19. Testing for one Generalized Linear Single Order Parameter

    DEFF Research Database (Denmark)

    Ellegaard, Niels Langager; Christensen, Tage Emil; Dyre, Jeppe

    work the order parameter may be chosen to have a non-exponential relaxation. The model predictions contradict the general consensus of the properties of viscous liquids in two ways: (i) The model predicts that following a linear isobaric temperature step, the normalized volume and entalpy relaxation...... functions are identical. This assumption conflicts with some (but not all) reports, utilizing the Tool-Narayanaswamy formalism to extrapolate from non-linear measurements to the linear regime. (ii) The model predicts that the theoretical "linear Prigogine-Defay" ratio is one. This ratio has never been...... responses or extrapolate from measurements of a glassy state away from equilibrium. Starting from a master equation description of inherent dynamics, we calculate the complex thermodynamic response functions. We device a way of testing for the generalized single order parameter model by measuring 3 complex...

  20. Generalized S-matrix in Mixed Representations

    CERN Document Server

    Ishikawa, K; Ishikawa, Kenzo; Shimomura, Takashi

    2006-01-01

    A generalized scattering amplitude where momenta of incoming-particles and outgoing-particles as well as positions of incoming-particles and outgoing-particles are specified is formulated. Idealistic beams and idealistic measuring instruments where momenta and positions satisfy minimum uncertainty are studied with a use of minimum wave packets, coherent states. In the present work, we show general features of the generalized scattering amplitudes based on ${\\phi}^4$ theory. We give a proof of completeness of many body states, asymptotic behaviors in the large distance region, and factorization of the amplitudes. Despite of the non-orthogonal properties of wave packets, we found that the probability interpretation is verified. A differential probability depends upon the wave packet size but a total probability that is integrated in the final states is independent from the size of final state wave packet and becomes universal. Few body amplitudes are studied as examples.

  1. Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations

    DEFF Research Database (Denmark)

    Tornøe, Christoffer Wenzel; Agersø, Henrik; Madsen, Henrik

    2004-01-01

    The standard software for non-linear mixed-effect analysis of pharmacokinetic/phar-macodynamic (PK/PD) data is NONMEM while the non-linear mixed-effects package NLME is an alternative as tong as the models are fairly simple. We present the nlmeODE package which combines the ordinary differential...... equation (ODE) solver package odesolve and the non-Linear mixed effects package NLME thereby enabling the analysis of complicated systems of ODEs by non-linear mixed-effects modelling. The pharmacokinetics of the anti-asthmatic drug theophylline is used to illustrate the applicability of the nlme...

  2. Estimation and variable selection for generalized additive partial linear models

    KAUST Repository

    Wang, Li

    2011-08-01

    We study generalized additive partial linear models, proposing the use of polynomial spline smoothing for estimation of nonparametric functions, and deriving quasi-likelihood based estimators for the linear parameters. We establish asymptotic normality for the estimators of the parametric components. The procedure avoids solving large systems of equations as in kernel-based procedures and thus results in gains in computational simplicity. We further develop a class of variable selection procedures for the linear parameters by employing a nonconcave penalized quasi-likelihood, which is shown to have an asymptotic oracle property. Monte Carlo simulations and an empirical example are presented for illustration. © Institute of Mathematical Statistics, 2011.

  3. Dynamic generalized linear models for monitoring endemic diseases

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, Dan Børge; Halasa, T.

    The objective was to use a Dynamic Generalized Linear Model (DGLM) based on abinomial distribution with a linear trend, for monitoring the PRRS (Porcine Reproductive and Respiratory Syndrome sero-prevalence in Danish swine herds. The DGLM was described and its performance for monitoring control...... in sero-prevalence. Based on this, it was possible to detect variations in the growth model component. This study is a proof-of-concept, demonstrating the use of DGLMs for monitoring endemic diseases. In addition, the principles stated might be useful in general research on monitoring and surveillance...

  4. A Matrix Approach for General Higher Order Linear Recurrences

    Science.gov (United States)

    2011-01-01

    properties of linear recurrences (such as the well-known Fibonacci and Pell sequences ). In [2], Er defined k linear recurring sequences of order at...the nth term of the ith generalized order-k Fibonacci sequence . Communicated by Lee See Keong. Received: March 26, 2009; Revised: August 28, 2009...6], the author gave the generalized order-k Fibonacci and Pell (F-P) sequence as follows: For m ≥ 0, n > 0 and 1 ≤ i ≤ k uin = 2 muin−1 + u i n−2

  5. Mixed Mode Oscillations due to the Generalized Canard Phenomenon

    DEFF Research Database (Denmark)

    Brøns, Morten; Krupa, Martin; Wechselberger, Martin

    2006-01-01

    Mixed mode oscillations combine features of small oscillations and large oscillations of relaxation type. We describe a mechanism for mixed mode oscillations based on the presence of canard solutions, which are trajectories passing from a stable to an unstable slow manifold. An important ingredient...... on mixed mode periodic orbits with Farey sequences of the form 1s. We also show how to generalize the context of one fast variable to an arbitrary number of fast variables....

  6. Linear generalized synchronization of chaotic systems with uncertain parameters

    Institute of Scientific and Technical Information of China (English)

    Jia Zhen

    2008-01-01

    A more general form of projective synchronization,so called linear generalized synchronization(LGS)is proposed,which includes the generalized projective synchronization(GPS)and the hybrid projective synchronization(HPS)as its special cases.Based on the adaptive technique and Lyapunov stability theory,a general method for achieving the LGS between two chaotic or hyperchaotic systems with uncertain parameters in any scaling matrix is presented.Some numerical simulations are provided to show the effectiveness and feasibility of the proposed synchronization method.

  7. Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

    Science.gov (United States)

    Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

    2015-09-01

    Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

  8. Klein-Gordon particles in mixed vector-scalar inversely linear potentials

    Energy Technology Data Exchange (ETDEWEB)

    Castro, Antonio S. de [UNESP, Campus de Guaratingueta, Departamento de Fisica e Quimica, Caixa Postal 205, 12516-410 Guaratingueta SP (Brazil)]. E-mail: castro@feg.unesp.br

    2005-04-25

    The problem of a spinless particle subject to a general mixing of vector and scalar inversely linear potentials in a two-dimensional world is analyzed. Exact bounded solutions are found in closed form by imposing boundary conditions on the eigenfunctions which ensure that the effective Hamiltonian is Hermitian for all the points of the space. The nonrelativistic limit of our results adds a new support to the conclusion that even-parity solutions to the nonrelativistic one-dimensional hydrogen atom do not exist.

  9. Solvability of Extended General Strongly Mixed Variational Inequalities

    Directory of Open Access Journals (Sweden)

    Balwant Singh Thakur

    2013-10-01

    Full Text Available In this paper, a new class of extended general strongly mixed variational inequalities is introduced and studied in Hilbert spaces. An existence theorem of solution is established and using resolvent operator technique, a new iterative algorithm for solving the extended general strongly mixed variational inequality is suggested. A convergence result for the iterative sequence generated by the new algorithm is also established.

  10. The Optimal Linear Combination of Multiple Predictors Under the Generalized Linear Models.

    Science.gov (United States)

    Jin, Hua; Lu, Ying

    2009-11-15

    Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It's important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher statistical utility. Under the generalized linear model for binary outcomes, the linear combination of multiple predictors in the link function is proved optimal in the sense that the area under the receiver operating characteristic (ROC) curve of this combination is the largest among all possible linear combination. The result was applied to analysis of the data from the Study of Osteoporotic Fractures (SOF) with comparison to Su and Liu's approach.

  11. The linear model and hypothesis a general unifying theory

    CERN Document Server

    Seber, George

    2015-01-01

    This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involve matrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality in the analysis of variance to other models, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.

  12. Thurstonian models for sensory discrimination tests as generalized linear models

    DEFF Research Database (Denmark)

    Brockhoff, Per B.; Christensen, Rune Haubo Bojesen

    2010-01-01

    Sensory discrimination tests such as the triangle, duo-trio, 2-AFC and 3-AFC tests produce binary data and the Thurstonian decision rule links the underlying sensory difference 6 to the observed number of correct responses. In this paper it is shown how each of these four situations can be viewed...... as a so-called generalized linear model. The underlying sensory difference 6 becomes directly a parameter of the statistical model and the estimate d' and it's standard error becomes the "usual" output of the statistical analysis. The d' for the monadic A-NOT A method is shown to appear as a standard...... linear contrast in a generalized linear model using the probit link function. All methods developed in the paper are implemented in our free R-package sensR (http://www.cran.r-project.org/package=sensR/). This includes the basic power and sample size calculations for these four discrimination tests...

  13. A random effects generalized linear model for reliability compositive evaluation

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments. The relevant algorithms are also provided. Simulation results manifest the soundness and effectiveness of the proposed model.

  14. RF Circuit linearity optimization using a general weak nonlinearity model

    NARCIS (Netherlands)

    Cheng, W.; Oude Alink, M.S.; Annema, Anne J.; Croon, Jeroen A.; Nauta, Bram

    2012-01-01

    This paper focuses on optimizing the linearity in known RF circuits, by exploring the circuit design space that is usually available in today’s deep submicron CMOS technologies. Instead of using brute force numerical optimizers we apply a generalized weak nonlinearity model that only involves AC

  15. The General Linear Model as Structural Equation Modeling

    Science.gov (United States)

    Graham, James M.

    2008-01-01

    Statistical procedures based on the general linear model (GLM) share much in common with one another, both conceptually and practically. The use of structural equation modeling path diagrams as tools for teaching the GLM as a body of connected statistical procedures is presented. A heuristic data set is used to demonstrate a variety of univariate…

  16. Applying the General Linear Model to Repeated Measures Problems.

    Science.gov (United States)

    Pohlmann, John T.; McShane, Michael G.

    The purpose of this paper is to demonstrate the use of the general linear model (GLM) in problems with repeated measures on a dependent variable. Such problems include pretest-posttest designs, multitrial designs, and groups by trials designs. For each of these designs, a GLM analysis is demonstrated wherein full models are formed and restrictions…

  17. A random effects generalized linear model for reliability compositive evaluation

    Institute of Scientific and Technical Information of China (English)

    ZHAO Hui; YU Dan

    2009-01-01

    This paper first proposes a random effects generalized linear model to evaluate the storage life of one kind of high reliable and small sample-sized products by combining multi-sources information of products coming from the same population but stored at different environments.The relevant algorithms are also provided.Simulation results manifest the soundness and effectiveness of the proposed model.

  18. A new heuristic algorithm for general integer linear programming problems

    Institute of Scientific and Technical Information of China (English)

    GAO Pei-wang; CAI Ying

    2006-01-01

    A new heuristic algorithm is proposed for solving general integer linear programming problems.In the algorithm,the objective function hyperplane is used as a cutting plane,and then by introducing a special set of assistant sets,an efficient heuristic search for the solution to the integer linear program is carried out in the sets on the objective function hyperplane.A simple numerical example shows that the algorithm is efficient for some problems,and therefore,of practical interest.

  19. Regularization Paths for Generalized Linear Models via Coordinate Descent

    Directory of Open Access Journals (Sweden)

    Jerome Friedman

    2010-02-01

    Full Text Available We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include ℓ1 (the lasso, ℓ2 (ridge regression and mixtures of the two (the elastic net. The algorithms use cyclical coordinate descent, computed along a regularization path. The methods can handle large problems and can also deal efficiently with sparse features. In comparative timings we find that the new algorithms are considerably faster than competing methods.

  20. On Self-Adaptive Method for General Mixed Variational Inequalities

    Directory of Open Access Journals (Sweden)

    Abdellah Bnouhachem

    2008-01-01

    Full Text Available We suggest and analyze a new self-adaptive method for solving general mixed variational inequalities, which can be viewed as an improvement of the method of (Noor 2003. Global convergence of the new method is proved under the same assumptions as Noor's method. Some preliminary computational results are given to illustrate the efficiency of the proposed method. Since the general mixed variational inequalities include general variational inequalities, quasivariational inequalities, and nonlinear (implicit complementarity problems as special cases, results proved in this paper continue to hold for these problems.

  1. Generalized non-linear strength theory and transformed stress space

    Institute of Scientific and Technical Information of China (English)

    YAO Yangping; LU Dechun; ZHOU Annan; ZOU Bo

    2004-01-01

    Based on the test data of frictional materials and previous research achievements in this field, a generalized non-linear strength theory (GNST) is proposed. It describes non-linear strength properties on the π-plane and the meridian plane using a unified formula, and it includes almost all the present non-linear strength theories, which can be used in just one material. The shape of failure function of the GNST is a smooth curve between the SMP criterion and the Mises criterion on the π-plane, and an exponential curve on the meridian plane. Through the transformed stress space based on the GNST, the combination of the GNST and various constitutive models using p and q as stress parameters can be realized simply and rationally in three-dimensional stress state.

  2. General expression for linear and nonlinear time series models

    Institute of Scientific and Technical Information of China (English)

    Ren HUANG; Feiyun XU; Ruwen CHEN

    2009-01-01

    The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.

  3. Computation of Optimal Monotonicity Preserving General Linear Methods

    KAUST Repository

    Ketcheson, David I.

    2009-07-01

    Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.

  4. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina

    2012-08-03

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  5. Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

    CERN Document Server

    Gottwald, Fabian; Ivanov, Sergei D; Kühn, Oliver

    2015-01-01

    Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation (GLE), which can be rigorously derived by means of a linear projection (LP) technique. Within this framework a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here we discuss that this task is most naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importa...

  6. Neural Generalized Predictive Control of a non-linear Process

    DEFF Research Database (Denmark)

    Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

    1998-01-01

    The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem....

  7. A general theory of linear cosmological perturbations: bimetric theories

    CERN Document Server

    Lagos, Macarena

    2016-01-01

    We implement the method developed in [1] to construct the most general parametrised action for linear cosmological perturbations of bimetric theories of gravity. Specifically, we consider perturbations around a homogeneous and isotropic background, and identify the complete form of the action invariant under diffeomorphism transformations, as well as the number of free parameters characterising this cosmological class of theories. We discuss, in detail, the case without derivative interactions, and compare our results with those found in massive bigravity.

  8. On the unitarity of linearized General Relativity coupled to matter

    CERN Document Server

    Atkins, Michael

    2010-01-01

    We consider the unitarity of the S-matrix for linearized General Relativity coupled to particle physics models. Taking renormalization group effects of the Planck mass into account, we find that the scale at which unitarity is violated is strongly dependent on the particle content of the theory. We find that the requirement that the S-matrix be unitary up to the scale at which quantum gravitational effects become strong implies a bound on the particle content of the model.

  9. Credibility analysis of risk classes by generalized linear model

    Science.gov (United States)

    Erdemir, Ovgucan Karadag; Sucu, Meral

    2016-06-01

    In this paper generalized linear model (GLM) and credibility theory which are frequently used in nonlife insurance pricing are combined for reliability analysis. Using full credibility standard, GLM is associated with limited fluctuation credibility approach. Comparison criteria such as asymptotic variance and credibility probability are used to analyze the credibility of risk classes. An application is performed by using one-year claim frequency data of a Turkish insurance company and results of credible risk classes are interpreted.

  10. Electromagnetic axial anomaly in a generalized linear sigma model

    Science.gov (United States)

    Fariborz, Amir H.; Jora, Renata

    2017-06-01

    We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.

  11. Estimation linear model using block generalized inverse of a matrix

    OpenAIRE

    Jasińska, Elżbieta; Preweda, Edward

    2013-01-01

    The work shows the principle of generalized linear model, point estimation, which can be used as a basis for determining the status of movements and deformations of engineering objects. The structural model can be put on any boundary conditions, for example, to ensure the continuity of the deformations. Estimation by the method of least squares was carried out taking into account the terms and conditions of the Gauss- Markov for quadratic forms stored using Lagrange function. The original sol...

  12. Residuals analysis of the generalized linear models for longitudinal data.

    Science.gov (United States)

    Chang, Y C

    2000-05-30

    The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated structure within the same subject. We showed that the conventional residuals plots for model diagnosis in longitudinal data could mislead a researcher into trusting the fitted model. A non-parametric method, named the Wald-Wolfowitz run test, was proposed to check the residuals plots both quantitatively and graphically. The rationale proposedin this paper is well illustrated with two real clinical studies in Taiwan.

  13. Renormalization in general theories with inter-generation mixing

    Energy Technology Data Exchange (ETDEWEB)

    Kniehl, Bernd A. [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Sirlin, Alberto [New York Univ., NY (United States). Dept. of Physics

    2011-11-15

    We derive general and explicit expressions for the unrenormalized and renormalized dressed propagators of fermions in parity-nonconserving theories with inter-generation mixing. The mass eigenvalues, the corresponding mass counterterms, and the effect of inter-generation mixing on their determination are discussed. Invoking the Aoki-Hioki-Kawabe-Konuma-Muta renormalization conditions and employing a number of very useful relations from Matrix Algebra, we show explicitly that the renormalized dressed propagators satisfy important physical properties. (orig.)

  14. On testing an unspecified function through a linear mixed effects model with multiple variance components.

    Science.gov (United States)

    Wang, Yuanjia; Chen, Huaihou

    2012-12-01

    We examine a generalized F-test of a nonparametric function through penalized splines and a linear mixed effects model representation. With a mixed effects model representation of penalized splines, we imbed the test of an unspecified function into a test of some fixed effects and a variance component in a linear mixed effects model with nuisance variance components under the null. The procedure can be used to test a nonparametric function or varying-coefficient with clustered data, compare two spline functions, test the significance of an unspecified function in an additive model with multiple components, and test a row or a column effect in a two-way analysis of variance model. Through a spectral decomposition of the residual sum of squares, we provide a fast algorithm for computing the null distribution of the test, which significantly improves the computational efficiency over bootstrap. The spectral representation reveals a connection between the likelihood ratio test (LRT) in a multiple variance components model and a single component model. We examine our methods through simulations, where we show that the power of the generalized F-test may be higher than the LRT, depending on the hypothesis of interest and the true model under the alternative. We apply these methods to compute the genome-wide critical value and p-value of a genetic association test in a genome-wide association study (GWAS), where the usual bootstrap is computationally intensive (up to 10(8) simulations) and asymptotic approximation may be unreliable and conservative. © 2012, The International Biometric Society.

  15. A mixed formulation finite element for linear thin shell analysis

    Science.gov (United States)

    Lee, S. W.; Wong, S. C.

    1982-01-01

    An eight node curved thin shell slement was tested. The element is based on the degenerate solid concept and the mixed formulation with the independent inplane and transverse shear strains. The number of unknown parameters in the assumed strains is chosen to alleviate the spurious constaining or locking effect. It is indicated that for a pinched cylindrical shell with diaphragmed ends and fixed ends the present element shows good performance.

  16. Comparative Study of Algorithms for Automated Generalization of Linear Objects

    Science.gov (United States)

    Azimjon, S.; Gupta, P. K.; Sukhmani, R. S. G. S.

    2014-11-01

    Automated generalization, rooted from conventional cartography, has become an increasing concern in both geographic information system (GIS) and mapping fields. All geographic phenomenon and the processes are bound to the scale, as it is impossible for human being to observe the Earth and the processes in it without decreasing its scale. To get optimal results, cartographers and map-making agencies develop set of rules and constraints, however these rules are under consideration and topic for many researches up until recent days. Reducing map generating time and giving objectivity is possible by developing automated map generalization algorithms (McMaster and Shea, 1988). Modification of the scale traditionally is a manual process, which requires knowledge of the expert cartographer, and it depends on the experience of the user, which makes the process very subjective as every user may generate different map with same requirements. However, automating generalization based on the cartographic rules and constrains can give consistent result. Also, developing automated system for map generation is the demand of this rapid changing world. The research that we have conveyed considers only generalization of the roads, as it is one of the indispensable parts of a map. Dehradun city, Uttarakhand state of India was selected as a study area. The study carried out comparative study of the generalization software sets, operations and algorithms available currently, also considers advantages and drawbacks of the existing software used worldwide. Research concludes with the development of road network generalization tool and with the final generalized road map of the study area, which explores the use of open source python programming language and attempts to compare different road network generalization algorithms. Thus, the paper discusses the alternative solutions for automated generalization of linear objects using GIS-technologies. Research made on automated of road network

  17. Generalized PID observer design for descriptor linear systems.

    Science.gov (United States)

    Wu, Ai-Guo; Duan, Guang-Ren; Fu, Yan-Ming

    2007-10-01

    A type of generalized proportional-integral-derivative observers is proposed for descriptor linear systems. Based on a general parametric solution to a type of generalized Sylvester matrix equations, a parametric design approach for such observers is established. The proposed approach provides parameterizations for all the observer gain matrices, gives the parametric expression for the corresponding left eigenvector matrix of the observer system matrix, realizes the elimination of impulsive behaviors, and guarantees the regularity of the observer system. The design method can offer all the degrees of design freedom, which can be utilized to achieve various desired system specifications and performances. In addition, a numerical example is employed to show the design procedure and illustrate the effect of the presented approach.

  18. General linear matrix model, Minkowski spacetime and the Standard Model

    CERN Document Server

    Belyea, Chris

    2010-01-01

    The Hermitian matrix model with general linear symmetry is argued to decouple into a finite unitary matrix model that contains metastable multidimensional lattice configurations and a fermion determinant. The simplest metastable state is a Hermitian Weyl kinetic operator of either handedness on a 3+1 D lattice with general nonlocal interactions. The Hermiticity produces 16 effective Weyl fermions by species doubling, 8 left- and 8 right-handed. These are identified with a Standard Model generation. Only local non-anomalous gauge fields within the soup of general fluctuations can survive at long distances, and the degrees of freedom for gauge fields of an $SU(8)_L X SU(8)_R$ GUT are present. Standard Model gauge symmetries associate with particular species symmetries, for example change of QCD color associates with permutation of doubling status amongst space directions. Vierbein gravity is probably also generated. While fundamental Higgs fields are not possible, low fermion current masses can arise from chira...

  19. Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

    Science.gov (United States)

    Gottwald, Fabian; Karsten, Sven; Ivanov, Sergei D.; Kühn, Oliver

    2015-06-01

    Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

  20. Parametrizing linear generalized Langevin dynamics from explicit molecular dynamics simulations

    Energy Technology Data Exchange (ETDEWEB)

    Gottwald, Fabian; Karsten, Sven; Ivanov, Sergei D., E-mail: sergei.ivanov@uni-rostock.de; Kühn, Oliver [Institute of Physics, Rostock University, Universitätsplatz 3, 18055 Rostock (Germany)

    2015-06-28

    Fundamental understanding of complex dynamics in many-particle systems on the atomistic level is of utmost importance. Often the systems of interest are of macroscopic size but can be partitioned into a few important degrees of freedom which are treated most accurately and others which constitute a thermal bath. Particular attention in this respect attracts the linear generalized Langevin equation, which can be rigorously derived by means of a linear projection technique. Within this framework, a complicated interaction with the bath can be reduced to a single memory kernel. This memory kernel in turn is parametrized for a particular system studied, usually by means of time-domain methods based on explicit molecular dynamics data. Here, we discuss that this task is more naturally achieved in frequency domain and develop a Fourier-based parametrization method that outperforms its time-domain analogues. Very surprisingly, the widely used rigid bond method turns out to be inappropriate in general. Importantly, we show that the rigid bond approach leads to a systematic overestimation of relaxation times, unless the system under study consists of a harmonic bath bi-linearly coupled to the relevant degrees of freedom.

  1. Confidence Intervals of Variance Functions in Generalized Linear Model

    Institute of Scientific and Technical Information of China (English)

    Yong Zhou; Dao-ji Li

    2006-01-01

    In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models (GLMs), when designs are fixed points and random variables respectively. Bias-corrected confidence bands are proposed for the (conditional) variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the (conditional) variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparametric autoregressive times series model with heteroscedastic conditional variance.

  2. Investigation of turbulent plane mixing layer using generalized differential quadrature

    Energy Technology Data Exchange (ETDEWEB)

    Basirat Tabrizi, H.; Rezaei Niya, S.M.; Fariborz, S.J. [Amirkabir Univ. of Tech., Mechanical Engineering Dept., Tehran (Iran, Islamic Republic of)]. E-mail: hbasirat@aut.ac.ir; H.Basirat@dal.ca

    2004-07-01

    There is considerable interest in two-dimensional turbulent mixing layer, to name a few e.g. nature, combustion chamber, premixers of gas turbine combustor and many other technological applications. There features are the presence of large vortical structure, free turbulent characteristics, asymptotic behavior, faster growth rate. Some of the parameters that are known to affect the mixing layer behavior are investigated through the numerical models and experimental analysis during these past decades. A suitable solution for turbulent plane mixing layer requires the use of variable mesh size and an appropriate discretization scheme. The Generalized Differential Quadrature (GDQ) method is utilized to solve the problem. It can be a tool for evaluating the equations obtained for plane mixing layer. The present approach works well by refining mesh size, simplifying the calculation algorithms and less time for calculation anticipated. The numerical simulation is compared with the reported numerical and experimental results of others. (author)

  3. Linear and nonlinear viscoelastic properties of bidisperse linear polymers: Mixing law and tube pressure effect

    DEFF Research Database (Denmark)

    van Ruymbeke, E.; Nielsen, J.; Hassager, Ole

    2010-01-01

    In this manuscript, we extend the tube-based model that we developed for predicting the linear viscoelasticity of entangled polymers [van Ruymbeke et al., J. Non-Newtonian Fluid Mech. 128, 7-22 (2005)] to the prediction of the extensional rheology of monodisperse and bidisperse linear polymers...

  4. A Graphical User Interface to Generalized Linear Models in MATLAB

    Directory of Open Access Journals (Sweden)

    Peter Dunn

    1999-07-01

    Full Text Available Generalized linear models unite a wide variety of statistical models in a common theoretical framework. This paper discusses GLMLAB-software that enables such models to be fitted in the popular mathematical package MATLAB. It provides a graphical user interface to the powerful MATLAB computational engine to produce a program that is easy to use but with many features, including offsets, prior weights and user-defined distributions and link functions. MATLAB's graphical capacities are also utilized in providing a number of simple residual diagnostic plots.

  5. Adaptive quasi-likelihood estimate in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    CHEN Xia; CHEN Xiru

    2005-01-01

    This paper gives a thorough theoretical treatment on the adaptive quasilikelihood estimate of the parameters in the generalized linear models. The unknown covariance matrix of the response variable is estimated by the sample. It is shown that the adaptive estimator defined in this paper is asymptotically most efficient in the sense that it is asymptotic normal, and the covariance matrix of the limit distribution coincides with the one for the quasi-likelihood estimator for the case that the covariance matrix of the response variable is completely known.

  6. Polymorphic Uncertain Linear Programming for Generalized Production Planning Problems

    Directory of Open Access Journals (Sweden)

    Xinbo Zhang

    2014-01-01

    Full Text Available A polymorphic uncertain linear programming (PULP model is constructed to formulate a class of generalized production planning problems. In accordance with the practical environment, some factors such as the consumption of raw material, the limitation of resource and the demand of product are incorporated into the model as parameters of interval and fuzzy subsets, respectively. Based on the theory of fuzzy interval program and the modified possibility degree for the order of interval numbers, a deterministic equivalent formulation for this model is derived such that a robust solution for the uncertain optimization problem is obtained. Case study indicates that the constructed model and the proposed solution are useful to search for an optimal production plan for the polymorphic uncertain generalized production planning problems.

  7. Generalized space and linear momentum operators in quantum mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Bruno G. da, E-mail: bruno.costa@ifsertao-pe.edu.br [Instituto Federal de Educação, Ciência e Tecnologia do Sertão Pernambucano, Campus Petrolina, BR 407, km 08, 56314-520 Petrolina, Pernambuco (Brazil); Instituto de Física, Universidade Federal da Bahia, R. Barão de Jeremoabo s/n, 40170-115 Salvador, Bahia (Brazil); Borges, Ernesto P., E-mail: ernesto@ufba.br [Instituto de Física, Universidade Federal da Bahia, R. Barão de Jeremoabo s/n, 40170-115 Salvador, Bahia (Brazil)

    2014-06-15

    We propose a modification of a recently introduced generalized translation operator, by including a q-exponential factor, which implies in the definition of a Hermitian deformed linear momentum operator p{sup ^}{sub q}, and its canonically conjugate deformed position operator x{sup ^}{sub q}. A canonical transformation leads the Hamiltonian of a position-dependent mass particle to another Hamiltonian of a particle with constant mass in a conservative force field of a deformed phase space. The equation of motion for the classical phase space may be expressed in terms of the generalized dual q-derivative. A position-dependent mass confined in an infinite square potential well is shown as an instance. Uncertainty and correspondence principles are analyzed.

  8. Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming

    Science.gov (United States)

    2016-01-01

    TECHNICAL REPORT NSWC PCD TR 2015-003 OPTIMIZED WATERSPACE MANAGEMENT AND SCHEDULING USING MIXED-INTEGER LINEAR PROGRAMMING...constraints required for the mathematical formulation of the MCM scheduling problem pertaining to the survey constraints and logistics management . The...Floudas, Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications, Oxford University Press, 1995. [10] M. J. Bays, A. Shende, D. J

  9. Generalized Ghost Dark Energy with Non-Linear Interaction

    CERN Document Server

    Ebrahimi, E; Mehrabi, A; Movahed, S M S

    2016-01-01

    In this paper we investigate ghost dark energy model in the presence of non-linear interaction between dark energy and dark matter. The functional form of dark energy density in the generalized ghost dark energy (GGDE) model is $\\rho_D\\equiv f(H, H^2)$ with coefficient of $H^2$ represented by $\\zeta$ and the model contains three free parameters as $\\Omega_D, \\zeta$ and $b^2$ (the coupling coefficient of interactions). We propose three kinds of non-linear interaction terms and discuss the behavior of equation of state, deceleration and dark energy density parameters of the model. We also find the squared sound speed and search for signs of stability of the model. To compare the interacting GGDE model with observational data sets, we use more recent observational outcomes, namely SNIa, gamma-ray bursts, baryonic acoustic oscillation and the most relevant CMB parameters including, the position of acoustic peaks, shift parameters and redshift to recombination. For GGDE with the first non-linear interaction, the j...

  10. Linear spin-2 fields in most general backgrounds

    CERN Document Server

    Bernard, Laura; Schmidt-May, Angnis; von Strauss, Mikael

    2015-01-01

    We derive the full perturbative equations of motion for the most general background solutions in ghost-free bimetric theory in its metric formulation. Clever field redefinitions at the level of fluctuations enable us to circumvent the problem of varying a square-root matrix appearing in the theory. This greatly simplifies the expressions for the linear variation of the bimetric interaction terms. We show that these field redefinitions exist and are uniquely invertible if and only if the variation of the square-root matrix itself has a unique solution, which is a requirement for the linearised theory to be well-defined. As an application of our results we examine the constraint structure of ghost-free bimetric theory at the level of linear equations of motion for the first time. We identify a scalar combination of equations which is responsible for the absence of the Boulware-Deser ghost mode in the theory. The bimetric scalar constraint is in general not manifestly covariant in its nature. However, in the mas...

  11. General quantum constraints on detector noise in continuous linear measurements

    Science.gov (United States)

    Miao, Haixing

    2017-01-01

    In quantum sensing and metrology, an important class of measurement is the continuous linear measurement, in which the detector is coupled to the system of interest linearly and continuously in time. One key aspect involved is the quantum noise of the detector, arising from quantum fluctuations in the detector input and output. It determines how fast we acquire information about the system and also influences the system evolution in terms of measurement backaction. We therefore often categorize it as the so-called imprecision noise and quantum backaction noise. There is a general Heisenberg-like uncertainty relation that constrains the magnitude of and the correlation between these two types of quantum noise. The main result of this paper is to show that, when the detector becomes ideal, i.e., at the quantum limit with minimum uncertainty, not only does the uncertainty relation takes the equal sign as expected, but also there are two new equalities. This general result is illustrated by using the typical cavity QED setup with the system being either a qubit or a mechanical oscillator. Particularly, the dispersive readout of a qubit state, and the measurement of mechanical motional sideband asymmetry are considered.

  12. Non-collinear wave mixing for non-linear ultrasonic detection of physical ageing in PVC

    NARCIS (Netherlands)

    Demcenko, A.; Akkerman, Remko; Nagy, P.B.; Loendersloot, Richard

    2012-01-01

    This work considers the characterization of linear PVC acoustic properties using a linear ultrasonic measurement technique and the non-collinear ultrasonic wave mixing technique for measurement of the physical ageing state in PVC. The immersion pulse-echo measurements were used to evaluate phase

  13. Mixed integer linear programming for maximum-parsimony phylogeny inference.

    Science.gov (United States)

    Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell

    2008-01-01

    Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.

  14. Bayesian Subset Modeling for High-Dimensional Generalized Linear Models

    KAUST Repository

    Liang, Faming

    2013-06-01

    This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  15. A new family of gauges in linearized general relativity

    Science.gov (United States)

    Esposito, Giampiero; Stornaiolo, Cosimo

    2000-05-01

    For vacuum Maxwell theory in four dimensions, a supplementary condition exists (due to Eastwood and Singer) which is invariant under conformal rescalings of the metric, in agreement with the conformal symmetry of the Maxwell equations. Thus, starting from the de Donder gauge, which is not conformally invariant but is the gravitational counterpart of the Lorenz gauge, one can consider, led by formal analogy, a new family of gauges in general relativity, which involve fifth-order covariant derivatives of metric perturbations. The admissibility of such gauges in the classical theory is first proven in the cases of linearized theory about flat Euclidean space or flat Minkowski spacetime. In the former, the general solution of the equation for the fulfillment of the gauge condition after infinitesimal diffeomorphisms involves a 3-harmonic 1-form and an inverse Fourier transform. In the latter, one needs instead the kernel of powers of the wave operator, and a contour integral. The analysis is also used to put restrictions on the dimensionless parameter occurring in the DeWitt supermetric, while the proof of admissibility is generalized to a suitable class of curved Riemannian backgrounds. Eventually, a non-local construction of the tensor field is obtained which makes it possible to achieve conformal invariance of the above gauges.

  16. Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture

    Science.gov (United States)

    Ingersoll, Thomas; Cole, Stephanie; Madren-Whalley, Janna; Booker, Lamont; Dorsey, Russell; Li, Albert; Salem, Harry

    2016-01-01

    Integrated Discrete Multiple Organ Co-culture (IDMOC) is emerging as an in-vitro alternative to in-vivo animal models for pharmacology studies. IDMOC allows dose-response relationships to be investigated at the tissue and organoid levels, yet, these relationships often exhibit responses that are far more complex than the binary responses often measured in whole animals. To accommodate departure from binary endpoints, IDMOC requires an expansion of analytic techniques beyond simple linear probit and logistic models familiar in toxicology. IDMOC dose-responses may be measured at continuous scales, exhibit significant non-linearity such as local maxima or minima, and may include non-independent measures. Generalized additive mixed-modeling (GAMM) provides an alternative description of dose-response that relaxes assumptions of independence and linearity. We compared GAMMs to traditional linear models for describing dose-response in IDMOC pharmacology studies. PMID:27110941

  17. Generalized Additive Mixed-Models for Pharmacology Using Integrated Discrete Multiple Organ Co-Culture.

    Directory of Open Access Journals (Sweden)

    Thomas Ingersoll

    Full Text Available Integrated Discrete Multiple Organ Co-culture (IDMOC is emerging as an in-vitro alternative to in-vivo animal models for pharmacology studies. IDMOC allows dose-response relationships to be investigated at the tissue and organoid levels, yet, these relationships often exhibit responses that are far more complex than the binary responses often measured in whole animals. To accommodate departure from binary endpoints, IDMOC requires an expansion of analytic techniques beyond simple linear probit and logistic models familiar in toxicology. IDMOC dose-responses may be measured at continuous scales, exhibit significant non-linearity such as local maxima or minima, and may include non-independent measures. Generalized additive mixed-modeling (GAMM provides an alternative description of dose-response that relaxes assumptions of independence and linearity. We compared GAMMs to traditional linear models for describing dose-response in IDMOC pharmacology studies.

  18. Explicit estimating equations for semiparametric generalized linear latent variable models

    KAUST Repository

    Ma, Yanyuan

    2010-07-05

    We study generalized linear latent variable models without requiring a distributional assumption of the latent variables. Using a geometric approach, we derive consistent semiparametric estimators. We demonstrate that these models have a property which is similar to that of a sufficient complete statistic, which enables us to simplify the estimating procedure and explicitly to formulate the semiparametric estimating equations. We further show that the explicit estimators have the usual root n consistency and asymptotic normality. We explain the computational implementation of our method and illustrate the numerical performance of the estimators in finite sample situations via extensive simulation studies. The advantage of our estimators over the existing likelihood approach is also shown via numerical comparison. We employ the method to analyse a real data example from economics. © 2010 Royal Statistical Society.

  19. Modeling local item dependence with the hierarchical generalized linear model.

    Science.gov (United States)

    Jiao, Hong; Wang, Shudong; Kamata, Akihito

    2005-01-01

    Local item dependence (LID) can emerge when the test items are nested within common stimuli or item groups. This study proposes a three-level hierarchical generalized linear model (HGLM) to model LID when LID is due to such contextual effects. The proposed three-level HGLM was examined by analyzing simulated data sets and was compared with the Rasch-equivalent two-level HGLM that ignores such a nested structure of test items. The results demonstrated that the proposed model could capture LID and estimate its magnitude. Also, the two-level HGLM resulted in larger mean absolute differences between the true and the estimated item difficulties than those from the proposed three-level HGLM. Furthermore, it was demonstrated that the proposed three-level HGLM estimated the ability distribution variance unaffected by the LID magnitude, while the two-level HGLM with no LID consideration increasingly underestimated the ability variance as the LID magnitude increased.

  20. dglars: An R Package to Estimate Sparse Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    Luigi Augugliaro

    2014-09-01

    Full Text Available dglars is a publicly available R package that implements the method proposed in Augugliaro, Mineo, and Wit (2013, developed to study the sparse structure of a generalized linear model. This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method proposed in Efron, Hastie, Johnstone, and Tibshirani (2004. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve: a predictor-corrector algorithm, proposed in Augugliaro et al. (2013, and a cyclic coordinate descent algorithm, proposed in Augugliaro, Mineo, and Wit (2012. The latter algorithm, as shown here, is significantly faster than the predictor-corrector algorithm. For comparison purposes, we have implemented both algorithms.

  1. Analysis of Robust Quasi-deviances for Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    Eva Cantoni

    2004-04-01

    Full Text Available Generalized linear models (McCullagh and Nelder 1989 are a popular technique for modeling a large variety of continuous and discrete data. They assume that the response variables Yi , for i = 1, . . . , n, come from a distribution belonging to the exponential family, such that E[Yi ] = ?i and V[Yi ] = V (?i , and that ?i = g(?i = xiT?, where ? ? IR p is the vector of parameters, xi ? IR p, and g(. is the link function. The non-robustness of the maximum likelihood and the maximum quasi-likelihood estimators has been studied extensively in the literature. For model selection, the classical analysis-of-deviance approach shares the same bad robustness properties. To cope with this, Cantoni and Ronchetti (2001 propose a robust approach based on robust quasi-deviance functions for estimation and variable selection. We refer to that paper for a deeper discussion and the review of the literature.

  2. Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

    Science.gov (United States)

    Row, Jeffrey R.; Knick, Steven T.; Oyler-McCance, Sara J.; Lougheed, Stephen C.; Fedy, Bradley C.

    2017-01-01

    Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

  3. Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations.

    Science.gov (United States)

    Row, Jeffrey R; Knick, Steven T; Oyler-McCance, Sara J; Lougheed, Stephen C; Fedy, Bradley C

    2017-06-01

    Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R(2) values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

  4. Non-differentiable multiobjective mixed symmetric duality under generalized convexity

    Directory of Open Access Journals (Sweden)

    Li Jueyou

    2011-01-01

    Full Text Available Abstract The objective of this paper is to obtain a mixed symmetric dual model for a class of non-differentiable multiobjective nonlinear programming problems where each of the objective functions contains a pair of support functions. Weak, strong and converse duality theorems are established for the model under some suitable assumptions of generalized convexity. Several special cases are also obtained. MS Classification: 90C32; 90C46.

  5. A New Family of Gauges in Linearized General Relativity

    CERN Document Server

    Esposito, G; Esposito, Giampiero; Stornaiolo, Cosimo

    2000-01-01

    For vacuum Maxwell theory in four dimensions, a supplementary condition exists (due to Eastwood and Singer) which is invariant under conformal rescalings of the metric, in agreement with the conformal symmetry of the Maxwell equations. Thus, starting from the de Donder gauge, which is not conformally invariant but is the gravitational counterpart of the Lorenz gauge, one can consider, led by formal analogy, a new family of gauges in general relativity, which involve fifth-order covariant derivatives of metric perturbations. The admissibility of such gauges in the classical theory is here proven in the cases of linearized theory about flat Euclidean space or flat Minkowski space-time. In the former, the general solution of the equation for the fulfillment of the gauge condition after infinitesimal diffeomorphisms involves a 3-harmonic function and an inverse Fourier transform. In the latter, one needs instead the kernel of powers of the wave operator, and a contour integral. The analysis is also used to put re...

  6. Generalized linear models with coarsened covariates: a practical Bayesian approach.

    Science.gov (United States)

    Johnson, Timothy R; Wiest, Michelle M

    2014-06-01

    Coarsened covariates are a common and sometimes unavoidable phenomenon encountered in statistical modeling. Covariates are coarsened when their values or categories have been grouped. This may be done to protect privacy or to simplify data collection or analysis when researchers are not aware of their drawbacks. Analyses with coarsened covariates based on ad hoc methods can compromise the validity of inferences. One valid method for accounting for a coarsened covariate is to use a marginal likelihood derived by summing or integrating over the unknown realizations of the covariate. However, algorithms for estimation based on this approach can be tedious to program and can be computationally expensive. These are significant obstacles to their use in practice. To overcome these limitations, we show that when expressed as a Bayesian probability model, a generalized linear model with a coarsened covariate can be posed as a tractable missing data problem where the missing data are due to censoring. We also show that this model is amenable to widely available general-purpose software for simulation-based inference for Bayesian probability models, providing researchers a very practical approach for dealing with coarsened covariates.

  7. Adaptive Error Estimation in Linearized Ocean General Circulation Models

    Science.gov (United States)

    Chechelnitsky, Michael Y.

    1999-01-01

    Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large

  8. Fermion Masses and Mixing in General Warped Extra Dimensional Models

    CERN Document Server

    Frank, Mariana; Pourtolami, Nima; Toharia, Manuel

    2015-01-01

    We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave-functions to small flavor breaking effects yield naturally hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor-blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the 5D neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is naturally more successful in generalized warped scenarios where the metric bac...

  9. Fermion masses and mixing in general warped extra dimensional models

    Science.gov (United States)

    Frank, Mariana; Hamzaoui, Cherif; Pourtolami, Nima; Toharia, Manuel

    2015-06-01

    We analyze fermion masses and mixing in a general warped extra dimensional model, where all the Standard Model (SM) fields, including the Higgs, are allowed to propagate in the bulk. In this context, a slightly broken flavor symmetry imposed universally on all fermion fields, without distinction, can generate the full flavor structure of the SM, including quarks, charged leptons and neutrinos. For quarks and charged leptons, the exponential sensitivity of their wave functions to small flavor breaking effects yield hierarchical masses and mixing as it is usual in warped models with fermions in the bulk. In the neutrino sector, the exponential wave-function factors can be flavor blind and thus insensitive to the small flavor symmetry breaking effects, directly linking their masses and mixing angles to the flavor symmetric structure of the five-dimensional neutrino Yukawa couplings. The Higgs must be localized in the bulk and the model is more successful in generalized warped scenarios where the metric background solution is different than five-dimensional anti-de Sitter (AdS5 ). We study these features in two simple frameworks, flavor complimentarity and flavor democracy, which provide specific predictions and correlations between quarks and leptons, testable as more precise data in the neutrino sector becomes available.

  10. Completely general bounds on Non-Unitary leptonic mixing

    CERN Document Server

    Hernandez-Garcia, Josu

    2016-01-01

    We derive constraints on the mixing of heavy right-handed neutrinos with the SM fields in the most general Seesaw scenario where the heavy neutrinos are integrated out. Among the electroweak and flavour observables included in the global fit, $\\mu\\rightarrow e\\gamma$ sets the present strongest bound on the additional neutrino mixing, while in the future it will be dominated by $\\mu-e$ conversion in nuclei. Increasing its sensitivity in future experiments could probe Non-Unitarity in Lepton Flavour Violating processes. Nevertheless, in order to determine completely model-independent constraints, we provide a second set of bounds derived through a global fit that does not include LFV observables. These indirect constraints on the off-diagonal elements come from the diagonal bounds through the Schwarz inequality.

  11. An H1-Galerkin Expanded Mixed Element Method for Semi-linear Hyperbolic Wave Equation

    Institute of Scientific and Technical Information of China (English)

    WANG Jin-feng; LIU Yang; LI Hong; HE Siriguleng

    2013-01-01

    An H1-Galerkin expanded mixed finite element method is discussed for a class of second order semi-linear hyperbolic wave equations.By using the mixed formulation,we can get the optimal approximation for three variables:the scalar unknown,its gradient and its flux(coefficient times the gradient),simultaneously.We also prove the existence and uniqueness of semi-discrete solution.Finally,we obtain some numerical results to illustrate the efficiency of the method.

  12. robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models

    Directory of Open Access Journals (Sweden)

    Manuel Koller

    2016-12-01

    Full Text Available As any real-life data, data modeled by linear mixed-effects models often contain outliers or other contamination. Even little contamination can drive the classic estimates far away from what they would be without the contamination. At the same time, datasets that require mixed-effects modeling are often complex and large. This makes it difficult to spot contamination. Robust estimation methods aim to solve both problems: to provide estimates where contamination has only little influence and to detect and flag contamination. We introduce an R package, robustlmm, to robustly fit linear mixed-effects models. The package's functions and methods are designed to closely equal those offered by lme4, the R package that implements classic linear mixed-effects model estimation in R. The robust estimation method in robustlmm is based on the random effects contamination model and the central contamination model. Contamination can be detected at all levels of the data. The estimation method does not make any assumption on the data's grouping structure except that the model parameters are estimable. robustlmm supports hierarchical and non-hierarchical (e.g., crossed grouping structures. The robustness of the estimates and their asymptotic efficiency is fully controlled through the function interface. Individual parts (e.g., fixed effects and variance components can be tuned independently. In this tutorial, we show how to fit robust linear mixed-effects models using robustlmm, how to assess the model fit, how to detect outliers, and how to compare different fits.

  13. Circuits and systems based on delta modulation linear, nonlinear and mixed mode processing

    CERN Document Server

    Zrilic, Djuro G

    2005-01-01

    This book is intended for students and professionals who are interested in the field of digital signal processing of delta-sigma modulated sequences. The overall focus is on the development of algorithms and circuits for linear, non-linear, and mixed mode processing of delta-sigma modulated pulse streams. The material presented here is directly relevant to applications in digital communication, DSP, instrumentation, and control.

  14. Statistical Modelling of Cardiovascular Data. An Introduction to Linear Mixed Models

    OpenAIRE

    Gonçalves, Paulo; Lenoir, Christophe; Heymes, Christophe; Swynghedauw, Bernard; Lavergne, Christian

    2005-01-01

    Most of statistical approaches in cardiovascular research were based on variance analysis (ANOVA). However, most of the time, the assumption that data are independent is violated since several measures are performed on the same subject (repeated measures). In addition, the presence of intra- and inter-observers variability can potentially obscure significant differences. The linear mixed model (LMM) is an extended multivariate linear regression method of analysis that accounts for both fixed ...

  15. The linearized inversion of the generalized interferometric multiple imaging

    KAUST Repository

    Aldawood, Ali

    2016-09-06

    The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.

  16. Bayesian inference for generalized linear models for spiking neurons

    Directory of Open Access Journals (Sweden)

    Sebastian Gerwinn

    2010-05-01

    Full Text Available Generalized Linear Models (GLMs are commonly used statistical methods for modelling the relationship between neural population activity and presented stimuli. When the dimension of the parameter space is large, strong regularization has to be used in order to fit GLMs to datasets of realistic size without overfitting. By imposing properly chosen priors over parameters, Bayesian inference provides an effective and principled approach for achieving regularization. Here we show how the posterior distribution over model parameters of GLMs can be approximated by a Gaussian using the Expectation Propagation algorithm. In this way, we obtain an estimate of the posterior mean and posterior covariance, allowing us to calculate Bayesian confidence intervals that characterize the uncertainty about the optimal solution. From the posterior we also obtain a different point estimate, namely the posterior mean as opposed to the commonly used maximum a posteriori estimate. We systematically compare the different inference techniques on simulated as well as on multi-electrode recordings of retinal ganglion cells, and explore the effects of the chosen prior and the performance measure used. We find that good performance can be achieved by choosing an Laplace prior together with the posterior mean estimate.

  17. Generalized Functional Linear Models With Semiparametric Single-Index Interactions

    KAUST Repository

    Li, Yehua

    2010-06-01

    We introduce a new class of functional generalized linear models, where the response is a scalar and some of the covariates are functional. We assume that the response depends on multiple covariates, a finite number of latent features in the functional predictor, and interaction between the two. To achieve parsimony, the interaction between the multiple covariates and the functional predictor is modeled semiparametrically with a single-index structure. We propose a two step estimation procedure based on local estimating equations, and investigate two situations: (a) when the basis functions are pre-determined, e.g., Fourier or wavelet basis functions and the functional features of interest are known; and (b) when the basis functions are data driven, such as with functional principal components. Asymptotic properties are developed. Notably, we show that when the functional features are data driven, the parameter estimates have an increased asymptotic variance, due to the estimation error of the basis functions. Our methods are illustrated with a simulation study and applied to an empirical data set, where a previously unknown interaction is detected. Technical proofs of our theoretical results are provided in the online supplemental materials.

  18. Multivariate statistical modelling based on generalized linear models

    CERN Document Server

    Fahrmeir, Ludwig

    1994-01-01

    This book is concerned with the use of generalized linear models for univariate and multivariate regression analysis. Its emphasis is to provide a detailed introductory survey of the subject based on the analysis of real data drawn from a variety of subjects including the biological sciences, economics, and the social sciences. Where possible, technical details and proofs are deferred to an appendix in order to provide an accessible account for non-experts. Topics covered include: models for multi-categorical responses, model checking, time series and longitudinal data, random effects models, and state-space models. Throughout, the authors have taken great pains to discuss the underlying theoretical ideas in ways that relate well to the data at hand. As a result, numerous researchers whose work relies on the use of these models will find this an invaluable account to have on their desks. "The basic aim of the authors is to bring together and review a large part of recent advances in statistical modelling of m...

  19. Generalized linear model for estimation of missing daily rainfall data

    Science.gov (United States)

    Rahman, Nurul Aishah; Deni, Sayang Mohd; Ramli, Norazan Mohamed

    2017-04-01

    The analysis of rainfall data with no missingness is vital in various applications including climatological, hydrological and meteorological study. The issue of missing data is a serious concern since it could introduce bias and lead to misleading conclusions. In this study, five imputation methods including simple arithmetic average, normal ratio method, inverse distance weighting method, correlation coefficient weighting method and geographical coordinate were used to estimate the missing data. However, these imputation methods ignored the seasonality in rainfall dataset which could give more reliable estimation. Thus this study is aimed to estimate the missingness in daily rainfall data by using generalized linear model with gamma and Fourier series as the link function and smoothing technique, respectively. Forty years daily rainfall data for the period from 1975 until 2014 which consists of seven stations at Kelantan region were selected for the analysis. The findings indicated that the imputation methods could provide more accurate estimation values based on the least mean absolute error, root mean squared error and coefficient of variation root mean squared error when seasonality in the dataset are considered.

  20. Generalized Mixed Equilibria, Variational Inclusions, and Fixed Point Problems

    Directory of Open Access Journals (Sweden)

    A. E. Al-Mazrooei

    2014-01-01

    Full Text Available We propose two iterative algorithms for finding a common element of the set of solutions of finite generalized mixed equilibrium problems, the set of solutions of finite variational inclusions for maximal monotone and inverse strong monotone mappings, and the set of common fixed points of infinite nonexpansive mappings and an asymptotically κ-strict pseudocontractive mapping in the intermediate sense in a real Hilbert space. We prove some strong and weak convergence theorems for the proposed iterative algorithms under suitable conditions.

  1. Logically rectangular mixed methods for Darcy flow on general geometry

    Energy Technology Data Exchange (ETDEWEB)

    Arbogast, T.; Keenan, P.T.; Wheeler, M.F.; Yotov, I. [Rice Univ., Houston, TX (United States)

    1995-12-31

    The authors consider an expanded mixed finite element formulation (cell centered finite difference) for Darcy flow with a tensor absolute permeability. The reservoir can be geometrically general with internal features, but the computational domain is rectangular. The method is defined on a curvilinear grid that need not be orthogonal, obtained by mapping the rectangular, computational grid. The original flow problem becomes a similar problem with a modified permeability on the computational grid. Quadrature rules turn the mixed method into a cell-centered finite difference method with a 9 point stencil in 2-D and 19 in 3-D. As shown by theory and experiment, if the modified permeability on the computational domain is smooth, then the convergence rate is optimal and both pressure and velocity are superconvergent at certain points. If not, Lagrange multiplier pressures can be introduced on boundaries of elements so that optimal convergence is retained. This modification presents only small changes in the solution process; in fact, the same parallel domain decomposition algorithms can be applied with little or no change to the code if the modified permeability is smooth over the subdomains. This Lagrange multiplier procedure can be used to extend the difference scheme to multi-block domains, and to give a coupling with unstructured grids. In all cases, the mixed formulation is locally conservative. Computational results illustrate the advantage and convergence of this method.

  2. Mixed Generalized Multiscale Finite Element Methods and Applications

    KAUST Repository

    Chung, Eric T.

    2015-03-03

    In this paper, we present a mixed generalized multiscale finite element method (GMsFEM) for solving flow in heterogeneous media. Our approach constructs multiscale basis functions following a GMsFEM framework and couples these basis functions using a mixed finite element method, which allows us to obtain a mass conservative velocity field. To construct multiscale basis functions for each coarse edge, we design a snapshot space that consists of fine-scale velocity fields supported in a union of two coarse regions that share the common interface. The snapshot vectors have zero Neumann boundary conditions on the outer boundaries, and we prescribe their values on the common interface. We describe several spectral decompositions in the snapshot space motivated by the analysis. In the paper, we also study oversampling approaches that enhance the accuracy of mixed GMsFEM. A main idea of oversampling techniques is to introduce a small dimensional snapshot space. We present numerical results for two-phase flow and transport, without updating basis functions in time. Our numerical results show that one can achieve good accuracy with a few basis functions per coarse edge if one selects appropriate offline spaces. © 2015 Society for Industrial and Applied Mathematics.

  3. Evaluation of a Linear Mixing Model to Retrieve Soil and Vegetation Temperatures of Land Targets

    NARCIS (Netherlands)

    Yang, J.; Jia, L.; Cui, Y.; Zhou, J.; Menenti, M.

    2014-01-01

    A simple linear mixing model of heterogeneous soil-vegetation system and retrieval of component temperatures from directional remote sensing measurements by inverting this model is evaluated in this paper using observations by a thermal camera. The thermal camera was used to obtain multi-angular TIR

  4. Moderate Deviations for M-estimators in Linear Models with φ-mixing Errors

    Institute of Scientific and Technical Information of China (English)

    Jun FAN

    2012-01-01

    In this paper,the moderate deviations for the M-estimators of regression parameter in a linear model are obtained when the errors form a strictly stationary φ-mixing sequence.The results are applied to study many different types of M-estimators such as Huber's estimator,Lp-regression estimator,least squares estimator and least absolute deviation estimator.

  5. A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates

    Science.gov (United States)

    Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.

    2012-01-01

    A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…

  6. A modified EM algorithm for estimation in generalized mixed models.

    Science.gov (United States)

    Steele, B M

    1996-12-01

    Application of the EM algorithm for estimation in the generalized mixed model has been largely unsuccessful because the E-step cannot be determined in most instances. The E-step computes the conditional expectation of the complete data log-likelihood and when the random effect distribution is normal, this expectation remains an intractable integral. The problem can be approached by numerical or analytic approximations; however, the computational burden imposed by numerical integration methods and the absence of an accurate analytic approximation have limited the use of the EM algorithm. In this paper, Laplace's method is adapted for analytic approximation within the E-step. The proposed algorithm is computationally straightforward and retains much of the conceptual simplicity of the conventional EM algorithm, although the usual convergence properties are not guaranteed. The proposed algorithm accommodates multiple random factors and random effect distributions besides the normal, e.g., the log-gamma distribution. Parameter estimates obtained for several data sets and through simulation show that this modified EM algorithm compares favorably with other generalized mixed model methods.

  7. Modeling continuous self-report measures of perceived emotion using generalized additive mixed models.

    Science.gov (United States)

    McKeown, Gary J; Sneddon, Ian

    2014-03-01

    Emotion research has long been dominated by the "standard method" of displaying posed or acted static images of facial expressions of emotion. While this method has been useful, it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose generalized additive models and generalized additive mixed models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The generalized additive mixed model approach is preferred, as it can account for autocorrelation in time series data and allows emotion decoding participants to be modeled as random effects. To increase confidence in linear differences, we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition, we provide comments on the use of generalized additive models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally, we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.

  8. A novel mixed-synchronization phenomenon in coupled Chua's circuits via non-fragile linear control

    Institute of Scientific and Technical Information of China (English)

    Wang Jun-Wei; Ma Qing-Hua; Zeng Li

    2011-01-01

    Dynamical variables of coupled nonlinear oscillators can exhibit different synchronization patterns depending on the designed coupling scheme.In this paper,a non-fragile linear feedback control strategy with multiplicative controller gain uncertainties is proposed for realizing the mixed-synchronization of Chua's circuits connected in a drive-response configuration.In particular,in the mixed-synchronization regime,different state variables of the response system can evolve into complete synchronization,anti-synchronization and even amplitude death simultaneously with the drive variables for an appropriate choice of scaling matrix.Using Lyapunov stability theory,we derive some sufficient criteria for achieving global mixed-synchronization.It is shown that the desired non-fragile state feedback controller can be constructed by solving a set of linear matrix inequalities(LMIs).Numerical simulations are also provided to demonstrate the effectiveness of the proposed control approach.

  9. Explicit mixed strain-displacement finite element for dynamic geometrically non-linear solid mechanics

    Science.gov (United States)

    Lafontaine, N. M.; Rossi, R.; Cervera, M.; Chiumenti, M.

    2015-03-01

    Low-order finite elements face inherent limitations related to their poor convergence properties. Such difficulties typically manifest as mesh-dependent or excessively stiff behaviour when dealing with complex problems. A recent proposal to address such limitations is the adoption of mixed displacement-strain technologies which were shown to satisfactorily address both problems. Unfortunately, although appealing, the use of such element technology puts a large burden on the linear algebra, as the solution of larger linear systems is needed. In this paper, the use of an explicit time integration scheme for the solution of the mixed strain-displacement problem is explored as an alternative. An algorithm is devised to allow the effective time integration of the mixed problem. The developed method retains second order accuracy in time and is competitive in terms of computational cost with the standard irreducible formulation.

  10. Prediction of an outcome using trajectories estimated from a linear mixed model.

    Science.gov (United States)

    Maruyama, Nami; Takahashi, Fumiaki; Takeuchi, Masahiro

    2009-09-01

    In longitudinal data, interest is usually focused on the repeatedly measured variable itself. In some situations, however, the pattern of variation of the variable over time may contain information about a separate outcome variable. In such situations, longitudinal data provide an opportunity to develop predictive models for future observations of the separate outcome variable given the current data for an individual. In particular, longitudinally changing patterns of repeated measurements of a variable measured up to time t, or trajectories, can be used to predict an outcome measure or event that occurs after time t. In this article, we propose a method for predicting an outcome variable based on a generalized linear model, specifically, a logistic regression model, the covariates of which are variables that characterize the trajectory of an individual. Since the trajectory of an individual contains estimation error, the proposed logistic regression model constitutes a measurement error model. The model is fitted in two steps. First, a linear mixed model is fitted to the longitudinal data to estimate the random effect that characterizes the trajectory for each individual while adjusting for other covariates. In the second step, a conditional likelihood approach is applied to account for the estimation error in the trajectory. Prediction of an outcome variable is based on the logistic regression model in the second step. The receiver operating characteristic curve is used to compare the discrimination ability of a model with trajectories to one without trajectories as covariates. A simulation study is used to assess the performance of the proposed method, and the method is applied to clinical trial data.

  11. Non-linear mixed models in the analysis of mediated longitudinal data with binary outcomes.

    Science.gov (United States)

    Blood, Emily A; Cheng, Debbie M

    2012-01-24

    Structural equation models (SEMs) provide a general framework for analyzing mediated longitudinal data. However when interest is in the total effect (i.e. direct plus indirect) of a predictor on the binary outcome, alternative statistical techniques such as non-linear mixed models (NLMM) may be preferable, particularly if specific causal pathways are not hypothesized or specialized SEM software is not readily available. The purpose of this paper is to evaluate the performance of the NLMM in a setting where the SEM is presumed optimal. We performed a simulation study to assess the performance of NLMMs relative to SEMs with respect to bias, coverage probability, and power in the analysis of mediated binary longitudinal outcomes. Both logistic and probit models were evaluated. Models were also applied to data from a longitudinal study assessing the impact of alcohol consumption on HIV disease progression. For the logistic model, the NLMM adequately estimated the total effect of a repeated predictor on the repeated binary outcome and were similar to the SEM across a variety of scenarios evaluating sample size, effect size, and distributions of direct vs. indirect effects. For the probit model, the NLMM adequately estimated the total effect of the repeated predictor, however, the probit SEM overestimated effects. Both logistic and probit NLMMs performed well relative to corresponding SEMs with respect to bias, coverage probability and power. In addition, in the probit setting, the NLMM may produce better estimates of the total effect than the probit SEM, which appeared to overestimate effects.

  12. NGPG-STABILITY OF LINEAR MULTISTEP METHODS FOR SYSTEMS OF GENERALIZED NEUTRAL DELAY DIFFERENTIAL EQUATIONS

    Institute of Scientific and Technical Information of China (English)

    丛玉豪

    2001-01-01

    The stability analysis of linear multistep methods for the numerical solutions of the systems of generalized neutral delay differential equations is discussed. The stability behaviour of linear multistep methods was analysed for the solution of the generalized system of linear neutral test equations. After the establishment of a sufficient condition for asymptotic stability of the solutions of the generalized system, it is shown that a linear multistep method is NGPG-stable if and only if it is A-stable.

  13. A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.

    Science.gov (United States)

    Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin

    2017-02-01

    The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed.

  14. GENERALIZED RICCATI TRANSFORMATION AND OSCILLATION FOR LINEAR DIFFERENTIAL EQUATIONS WITH DAMPING

    Institute of Scientific and Technical Information of China (English)

    ZhengZhaowen; LiuJingzhao

    2005-01-01

    Using generalized Riccati transformation, some new oscillation criteria for damped linear differential equations are established. These results improve and generalize some known oscillation criteria due to A.Wintner [8], I.V.Kamenev [10] for the undamped linear differential equations, and Sobol [3], J.S.W.Wong [1] for the damped linear differential equations.

  15. Admissible Estimators in the General Multivariate Linear Model with Respect to Inequality Restricted Parameter Set

    Directory of Open Access Journals (Sweden)

    Liu Gang

    2009-01-01

    Full Text Available By using the methods of linear algebra and matrix inequality theory, we obtain the characterization of admissible estimators in the general multivariate linear model with respect to inequality restricted parameter set. In the classes of homogeneous and general linear estimators, the necessary and suffcient conditions that the estimators of regression coeffcient function are admissible are established.

  16. Generalized (,,-Pairs for Uncertain Linear Infinite-Dimensional Systems

    Directory of Open Access Journals (Sweden)

    Naohisa Otsuka

    2009-01-01

    Full Text Available We introduce the concept of generalized (,,-pairs which is related to generalized (,-invariant subspaces and generalized (,-invariant subspaces for infinite-dimensional systems. As an application the parameter-insensitive disturbance-rejection problem with dynamic compensator is formulated and its solvability conditions are presented. Further, an illustrative example is also examined.

  17. Connections between Generalizing and Justifying: Students' Reasoning with Linear Relationships

    Science.gov (United States)

    Ellis, Amy B.

    2007-01-01

    Research investigating algebra students' abilities to generalize and justify suggests that they experience difficulty in creating and using appropriate generalizations and proofs. Although the field has documented students' errors, less is known about what students do understand to be general and convincing. This study examines the ways in which…

  18. A NEW CLASS OF BILEVEL GENERALIZED MIXED EQUILIBRIUM PROBLEMS IN BANACH SPACES

    Institute of Scientific and Technical Information of China (English)

    Ding Xieping

    2012-01-01

    A new class of bilevel generalized mixed equilibrium problems involving setvalued mappings is introduced and studied in a real Banach space.By using the auxiliary principle technique,new iterative algorithms for solving the generalized mixed equilibrium problems and bilevel generalized mixed equilibrium problems involving set-valued mappings are suggested and analyzed.Existence of solutions and strong convergence of the iterative sequences generated by the algorithms are proved under quite mild conditions.The behavior of the solution set of the generalized mixed equilibrium problems and bilevel generalized mixed equilibrium problems is also discussed.These results are new and generalize some recent results in this field.

  19. Linear theory of the response of Na mixing ratio to gravity waves

    Institute of Scientific and Technical Information of China (English)

    XU Jiyao; JI Qiao; WU Mingliang

    2003-01-01

    The influence of gravity waves on the sodium layer is studied by using a linear photochemical-dynamical coupling gravity wave model. The model includes the background photochemistry and the photochemical reactions in the sodium layer. The amplitude and phase difference of the response of sodium mixing ratio to gravity waves are calculated. The results indicate that the lower part of sodium layer is the most sensitive region responding to gravity waves. The perturbation of sodium mixing ratio is in phase with temperature in the lower part of the layer. However, it is out of phase with temperature fluctuation in the upper part.

  20. Inferring fixed effects in a mixed linear model from an integrated likelihood

    DEFF Research Database (Denmark)

    Gianola, Daniel; Sorensen, Daniel

    2008-01-01

    of all nuisances, viewing random effects and variance components as missing data. In a simulation of a grazing trial, the procedure was compared with four widely used estimators of fixed effects in mixed models, and found to be competitive. An analysis of body weight in freshwater crayfish was conducted......A new method for likelihood-based inference of fixed effects in mixed linear models, with variance components treated as nuisance parameters, is presented. The method uses uniform-integration of the likelihood; the implementation employs the expectation-maximization (EM) algorithm for elimination...

  1. Mixed H2/H∞ Optimal Guaranteed Cost Control of Uncertain Linear Systems

    Institute of Scientific and Technical Information of China (English)

    GuodingChen; MayingYang; LiYu

    2004-01-01

    The mixed H2/H∞ guaranteed cost control problem via state feedback control laws is considered in this paper for linear systems with norm-bounded parameter uncertainty. Based on the linear matrix inequality (LMI) approach, sufficient conditions are derived for the existence of guaranteed cost controllers whihc guarantee not only a prespecified H∞ disturbance attenuation level on one controlled output for all admissible parameter uncertainties, but also the worst-case H2 performance index on the other controlled output to be no more than a specified bound. Furthermore, a convex optimization problem is formulated to design an optimal H2/H∞ guaranteed cost controller.

  2. A General Linear Method for Equating with Small Samples

    Science.gov (United States)

    Albano, Anthony D.

    2015-01-01

    Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated…

  3. PYESSENCE: Generalized Coupled Quintessence Linear Perturbation Python Code

    Science.gov (United States)

    Leithes, Alexander

    2016-09-01

    PYESSENCE evolves linearly perturbed coupled quintessence models with multiple (cold dark matter) CDM fluid species and multiple DE (dark energy) scalar fields, and can be used to generate quantities such as the growth factor of large scale structure for any coupled quintessence model with an arbitrary number of fields and fluids and arbitrary couplings.

  4. Hyperspectral unmixing with spectral variability using a perturbed linear mixing model

    CERN Document Server

    Thouvenin, Pierre-Antoine; Tourneret, Jean-Yves

    2015-01-01

    Given a mixed hyperspectral data set, linear unmixing aims at estimating the reference spectral signatures composing the data - referred to as endmembers - their abundance fractions and their number. In practice, the identified endmembers can vary spectrally within a given image and can thus be construed as variable instances of reference endmembers. Ignoring this variability induces estimation errors that are propagated into the unmixing procedure. To address this issue, endmember variability estimation consists of estimating the reference spectral signatures from which the estimated endmembers have been derived as well as their variability with respect to these references. This paper introduces a new linear mixing model that explicitly accounts for spatial and spectral endmember variabilities. The parameters of this model can be estimated using an optimization algorithm based on the alternating direction method of multipliers. The performance of the proposed unmixing method is evaluated on synthetic and rea...

  5. Mixed-field orientation of a thermal ensemble of linear polar molecules

    CERN Document Server

    Omiste, Juan J

    2013-01-01

    We present a theoretical study of the impact of an electrostatic field combined with nonresonant linearly polarized laser pulses on the rotational dynamics of a thermal ensemble of linear molecules. We solve the time-dependent Schr\\"odinger equation within the rigid rotor approximation for several rotational states. Using the carbonyl sulfide (OCS) molecule as a prototype, the mixed-field orientation of a thermal sample is analyzed in detail for experimentally accessible static field strengths and laser pulses. We demonstrate that for the characteristic field configuration used in current mixed-field orientation experiments, a significant orientation is obtained for rotational temperatures below 0.7K or using stronger dc fields.

  6. Winsorization on linear mixed model (Case study: National exam of senior high school in West Java)

    Science.gov (United States)

    Yuliyani, Leny; Kurnia, Anang; Indahwati

    2017-03-01

    In the case of hierarchical data is typically modeled with linear mixed model (LMM). The LMM requires the assumption of normality which is error and random effects are assumed normal distribution. However in practice, to meet the assumption of normality is difficult especially if the sample is small. Violation of the normality assumption can be caused by outliers. In this paper, we will examine the effect of outliers on the random effects and error and overcome them with the Winsorization technique. The result of application indicated that Winsorization technique with c-tuning constant iterative process produced root mean squared error, AIC, and BIC are smaller than the others. We conclude that Winsorization technique can be used to overcome outliers in linear mixed model fitting.

  7. Short communication: Alteration of priors for random effects in Gaussian linear mixed model

    DEFF Research Database (Denmark)

    Vandenplas, Jérémie; Christensen, Ole Fredslund; Gengler, Nicholas

    2014-01-01

    , multiple-trait predictions of lactation yields, and Bayesian approaches integrating external information into genetic evaluations) need to alter both the mean and (co)variance of the prior distributions and, to our knowledge, most software packages available in the animal breeding community do not permit......Linear mixed models, for which the prior multivariate normal distributions of random effects are assumed to have a mean equal to 0, are commonly used in animal breeding. However, some statistical analyses (e.g., the consideration of a population under selection into a genomic scheme breeding...... such alterations. Therefore, the aim of this study was to propose a method to alter both the mean and (co)variance of the prior multivariate normal distributions of random effects of linear mixed models while using currently available software packages. The proposed method was tested on simulated examples with 3...

  8. An SDP Approach for Multiperiod Mixed 0–1 Linear Programming Models with Stochastic Dominance Constraints for Risk Management

    DEFF Research Database (Denmark)

    Escudero, Laureano F.; Monge, Juan Francisco; Morales, Dolores Romero

    2015-01-01

    In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multist...

  9. Linearizability of Nonlinear Third-Order Ordinary Differential Equations by Using a Generalized Linearizing Transformation

    OpenAIRE

    Thailert, E.; Suksern, S.

    2014-01-01

    We discuss the linearization problem of third-order ordinary differential equation under the generalized linearizing transformation. We identify the form of the linearizable equations and the conditions which allow the third-order ordinary differential equation to be transformed into the simplest linear equation. We also illustrate how to construct the generalized linearizing transformation. Some examples of linearizable equation are provided to demonstrate our procedure.

  10. Maximum Likelihood in a Generalized Linear Finite Mixture Model by Using the EM Algorithm

    NARCIS (Netherlands)

    Jansen, R.C.

    A generalized linear finite mixture model and an EM algorithm to fit the model to data are described. By this approach the finite mixture model is embedded within the general framework of generalized linear models (GLMs). Implementation of the proposed EM algorithm can be readily done in statistical

  11. Study of D~0-D~0 mixing at a giga-Z linear collider

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The possibility of studying D 0-D 0 mixing at a giga-Z linear collider "Z factory" where 10 9 hadronic Z 0 decays can be accumulated is examined.We discuss the sensitivity for the measurements of neutral D mixing parameters.These results are compared to those attainable at B factories.We find that the typical decay length of the neutral D mesons at Z factory is about 10 times larger than that at B factory.In addition,the resolution of the vertex detector of a giga-Z factory is 2-3 times better than that of B factory.The proper time resolution at Z factory is about 20-30 times better than that at B factory.Therefore the determination of the mixing parameters at a giga-Z factory is more precise.

  12. A latent factor linear mixed model for high-dimensional longitudinal data analysis.

    Science.gov (United States)

    An, Xinming; Yang, Qing; Bentler, Peter M

    2013-10-30

    High-dimensional longitudinal data involving latent variables such as depression and anxiety that cannot be quantified directly are often encountered in biomedical and social sciences. Multiple responses are used to characterize these latent quantities, and repeated measures are collected to capture their trends over time. Furthermore, substantive research questions may concern issues such as interrelated trends among latent variables that can only be addressed by modeling them jointly. Although statistical analysis of univariate longitudinal data has been well developed, methods for modeling multivariate high-dimensional longitudinal data are still under development. In this paper, we propose a latent factor linear mixed model (LFLMM) for analyzing this type of data. This model is a combination of the factor analysis and multivariate linear mixed models. Under this modeling framework, we reduced the high-dimensional responses to low-dimensional latent factors by the factor analysis model, and then we used the multivariate linear mixed model to study the longitudinal trends of these latent factors. We developed an expectation-maximization algorithm to estimate the model. We used simulation studies to investigate the computational properties of the expectation-maximization algorithm and compare the LFLMM model with other approaches for high-dimensional longitudinal data analysis. We used a real data example to illustrate the practical usefulness of the model. Copyright © 2013 John Wiley & Sons, Ltd.

  13. Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

    Science.gov (United States)

    Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

    2016-01-01

    Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather

  14. Generalized linear IgA dermatosis with palmar involvement

    OpenAIRE

    Norris, Ivy N; Haeberle, M Tye; Callen, Jeffrey P.; Malone, Janine C

    2015-01-01

    Linear IgA bullous dermatosis (LABD) is a sub-epidermal blistering disorder characterized by deposition of IgA along the basement membrane zone (BMZ) as detected by immunofluorescence microscopy. The diagnosis is made by clinicopathologic correlation with immunofluorescence confirmation. Differentiation from other bullous dermatoses is important because therapeutic measures differ. Prompt initiation of the appropriate therapies can have a major impact on outcomes. We present three cases with ...

  15. Generalizing a categorization of students' interpretations of linear kinematics graphs

    Science.gov (United States)

    Bollen, Laurens; De Cock, Mieke; Zuza, Kristina; Guisasola, Jenaro; van Kampen, Paul

    2016-06-01

    We have investigated whether and how a categorization of responses to questions on linear distance-time graphs, based on a study of Irish students enrolled in an algebra-based course, could be adopted and adapted to responses from students enrolled in calculus-based physics courses at universities in Flanders, Belgium (KU Leuven) and the Basque Country, Spain (University of the Basque Country). We discuss how we adapted the categorization to accommodate a much more diverse student cohort and explain how the prior knowledge of students may account for many differences in the prevalence of approaches and success rates. Although calculus-based physics students make fewer mistakes than algebra-based physics students, they encounter similar difficulties that are often related to incorrectly dividing two coordinates. We verified that a qualitative understanding of kinematics is an important but not sufficient condition for students to determine a correct value for the speed. When comparing responses to questions on linear distance-time graphs with responses to isomorphic questions on linear water level versus time graphs, we observed that the context of a question influences the approach students use. Neither qualitative understanding nor an ability to find the slope of a context-free graph proved to be a reliable predictor for the approach students use when they determine the instantaneous speed.

  16. Principal component regression and linear mixed model in association analysis of structured samples: competitors or complements?

    Science.gov (United States)

    Zhang, Yiwei; Pan, Wei

    2015-03-01

    Genome-wide association studies (GWAS) have been established as a major tool to identify genetic variants associated with complex traits, such as common diseases. However, GWAS may suffer from false positives and false negatives due to confounding population structures, including known or unknown relatedness. Another important issue is unmeasured environmental risk factors. Among many methods for adjusting for population structures, two approaches stand out: one is principal component regression (PCR) based on principal component analysis, which is perhaps the most popular due to its early appearance, simplicity, and general effectiveness; the other is based on a linear mixed model (LMM) that has emerged recently as perhaps the most flexible and effective, especially for samples with complex structures as in model organisms. As shown previously, the PCR approach can be regarded as an approximation to an LMM; such an approximation depends on the number of the top principal components (PCs) used, the choice of which is often difficult in practice. Hence, in the presence of population structure, the LMM appears to outperform the PCR method. However, due to the different treatments of fixed vs. random effects in the two approaches, we show an advantage of PCR over LMM: in the presence of an unknown but spatially confined environmental confounder (e.g., environmental pollution or lifestyle), the PCs may be able to implicitly and effectively adjust for the confounder whereas the LMM cannot. Accordingly, to adjust for both population structures and nongenetic confounders, we propose a hybrid method combining the use and, thus, strengths of PCR and LMM. We use real genotype data and simulated phenotypes to confirm the above points, and establish the superior performance of the hybrid method across all scenarios.

  17. Non-linear mixed models in the analysis of mediated longitudinal data with binary outcomes

    Directory of Open Access Journals (Sweden)

    Blood Emily A

    2012-01-01

    Full Text Available Abstract Background Structural equation models (SEMs provide a general framework for analyzing mediated longitudinal data. However when interest is in the total effect (i.e. direct plus indirect of a predictor on the binary outcome, alternative statistical techniques such as non-linear mixed models (NLMM may be preferable, particularly if specific causal pathways are not hypothesized or specialized SEM software is not readily available. The purpose of this paper is to evaluate the performance of the NLMM in a setting where the SEM is presumed optimal. Methods We performed a simulation study to assess the performance of NLMMs relative to SEMs with respect to bias, coverage probability, and power in the analysis of mediated binary longitudinal outcomes. Both logistic and probit models were evaluated. Models were also applied to data from a longitudinal study assessing the impact of alcohol consumption on HIV disease progression. Results For the logistic model, the NLMM adequately estimated the total effect of a repeated predictor on the repeated binary outcome and were similar to the SEM across a variety of scenarios evaluating sample size, effect size, and distributions of direct vs. indirect effects. For the probit model, the NLMM adequately estimated the total effect of the repeated predictor, however, the probit SEM overestimated effects. Conclusions Both logistic and probit NLMMs performed well relative to corresponding SEMs with respect to bias, coverage probability and power. In addition, in the probit setting, the NLMM may produce better estimates of the total effect than the probit SEM, which appeared to overestimate effects.

  18. Slow relaxation of the magnetization in non-linear optical active layered mixed metal oxalate chains.

    Science.gov (United States)

    Cariati, Elena; Ugo, Renato; Santoro, Giuseppe; Tordin, Elisa; Sorace, Lorenzo; Caneschi, Andrea; Sironi, Angelo; Macchi, Piero; Casati, Nicola

    2010-12-06

    New Co(II) members of the family of multifunctional materials of general formula [DAMS](4)[M(2)Co(C(2)O(4))(6)]·2DAMBA·2H(2)O (M(III) = Rh, Fe, Cr; DAMBA = para-dimethylaminobenzaldehyde and [DAMS(+)] = trans-4-(4-dimethylaminostyryl)-1-methylpyridinium) have been isolated and characterized. Such new hybrid mixed metal oxalates are isostructural with the previously investigated containing Zn(II), Mn(II), and Ni(II). This allows to preserve the exceptional second harmonic generation (SHG) activity, due to both the large molecular quadratic hyperpolarizability of [DAMS(+)] and the efficiency of the crystalline network which organizes [DAMS(+)] into head-to-tail arranged J-type aggregates, and to further tune the magnetic properties. In particular, the magnetic data of the Rh(III) derivative demonstrate that high spin octacoordinated Co(II) centers behave very similarly to the hexacoordinated Co(II) ones, being dominated by a large orbital contribution. The Cr(III) derivative is characterized by ferromagnetic Cr(III)-Co(II) interactions. Most relevantly, the Fe(III) compound is characterized by a moderate antiferromagnetic interaction between Fe(III) and Co(II), resulting in a ferrimagnetic like structure. Its low temperature dynamic magnetic properties were found to follow a thermally activated behavior (τ(0) = 8.6 × 10(-11) s and ΔE = 21.4 K) and make this a candidate for the second oxalate-based single chain magnet (SCM) reported up to date, a property which in this case is coupled to the second order non linear optical (NLO) ones.

  19. A New General System of Generalized Nonlinear Mixed Composite-Type Equilibria and Fixed Point Problems with an Application to Minimization Problems

    Directory of Open Access Journals (Sweden)

    Pongsakorn Sunthrayuth

    2012-01-01

    Full Text Available We introduce a new general system of generalized nonlinear mixed composite-type equilibria and propose a new iterative scheme for finding a common element of the set of solutions of a generalized equilibrium problem, the set of solutions of a general system of generalized nonlinear mixed composite-type equilibria, and the set of fixed points of a countable family of strict pseudocontraction mappings. Furthermore, we prove the strong convergence theorem of the purposed iterative scheme in a real Hilbert space. As applications, we apply our results to solve a certain minimization problem related to a strongly positive bounded linear operator. Finally, we also give a numerical example which supports our results. The results obtained in this paper extend the recent ones announced by many others.

  20. Generalized linear IgA dermatosis with palmar involvement.

    Science.gov (United States)

    Norris, Ivy N; Haeberle, M Tye; Callen, Jeffrey P; Malone, Janine C

    2015-09-17

    Linear IgA bullous dermatosis (LABD) is a sub-epidermal blistering disorder characterized by deposition of IgA along the basement membrane zone (BMZ) as detected by immunofluorescence microscopy. The diagnosis is made by clinicopathologic correlation with immunofluorescence confirmation. Differentiation from other bullous dermatoses is important because therapeutic measures differ. Prompt initiation of the appropriate therapies can have a major impact on outcomes. We present three cases with prominent palmar involvement to alert the clinician of this potential physical exam finding and to consider LABD in the right context.

  1. A Modified Linear-Mixing Method for Calculating Atmospheric Path Radiances of Aerosol Mixtures

    Science.gov (United States)

    Abdou, W. A.; Martonchik, J. V.; Kahn, R. A.; West, R. A.; Diner, D. J.

    1997-01-01

    The top-of-atmosphere (TOA) path radiance generated by an aerosol mixture can be synthesized by linearly adding the contributions of the individual aerosol components, weighted by their fractional optical depths. The method, known as linear mixing, is exact in the single-scattering limit. When multiple scattering is significant, the method reproduces the atmospheric path radiance of the mixture with less than 3% errors for weakly absorbing aerosols up to optical thickness of 0.5. However, when strongly absorbing aerosols are included in the mixture, the errors are much larger. This is due to neglecting the effect of multiple interactions between the aerosol components, especially when the values of the single-scattering albedos of these components are so different that the parameter e = the sum of f(sub i)[(bar)omega(sub i) - (bar)omega(sub mix)]/(bar)omega(sub i) is larger than approximately 0.1, where (bar)omega(sub i)and f(sub i) are the single-scattering albedo and the fractional abundance of the ith component, and (bar)omega(sub mix) is the effective single-scattering albedo of the Mixture. We describe an empirical, modified linear-mixing method which effectively accounts for the multiple interactions between aerosol components. The modified and standard methods are identical when epsilon = 0.0 and give similar results when epsilon is less than or equal to 0.05. For optical depths larger than approximately 0.5, or when epsilon is greater than 0.05, only the modified method can reproduce the radiances within 5% error for common aerosol types up to optical thickness of 2.0. Because this method facilitates efficient and accurate atmospheric path radiance calculations for mixtures of a wide variety of aerosol types, it will be used as part of the aerosol retrieval methodology for the Earth Observing System (EOS) multiangle imaging spectroradiometer (MISR), scheduled for launch into polar orbit in 1998.

  2. A general algorithm for computing distance transforms in linear time

    NARCIS (Netherlands)

    Meijster, A.; Roerdink, J.B.T.M.; Hesselink, W.H.; Goutsias, J; Vincent, L; Bloomberg, DS

    2000-01-01

    A new general algorithm fur computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the com

  3. A general algorithm for computing distance transforms in linear time

    NARCIS (Netherlands)

    Meijster, A.; Roerdink, J.B.T.M.; Hesselink, W.H.; Goutsias, J; Vincent, L; Bloomberg, DS

    2000-01-01

    A new general algorithm fur computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the

  4. The general RF tuning for IH-DTL linear accelerators

    Science.gov (United States)

    Lu, Y. R.; Ratzinger, U.; Schlitt, B.; Tiede, R.

    2007-11-01

    The RF tuning is the most important research for achieving the resonant frequency and the flatness of electric field distributions along the axis of RF accelerating structures. The six different tuning concepts and that impacts on the longitudinal field distributions have been discussed in detail combining the RF tuning process of a 1:2 modeled 20.85 MV compact IH-DTL cavity, which was designed to accelerate proton, helium, oxygen or C 4+ from 400 keV/ u to 7 MeV/u and used as the linear injector of 430 MeV/ u synchrotron [Y.R. Lu, S. Minaev, U. Ratzinger, B. Schlitt, R.Tiede, The Compact 20MV IH-DTL for the Heidelberg Therapy Facility, in: Proceedings of the LINAC Conference, Luebeck, Germany, 2004 [1]; Y.R. Lu, Frankfurt University Dissertation, 2005. [2

  5. Application of generalized separation of variables to solving mixed problems with irregular boundary conditions

    Science.gov (United States)

    Gasymov, E. A.; Guseinova, A. O.; Gasanova, U. N.

    2016-07-01

    One of the methods for solving mixed problems is the classical separation of variables (the Fourier method). If the boundary conditions of the mixed problem are irregular, this method, generally speaking, is not applicable. In the present paper, a generalized separation of variables and a way of application of this method to solving some mixed problems with irregular boundary conditions are proposed. Analytical representation of the solution to this irregular mixed problem is obtained.

  6. The general RF tuning for IH-DTL linear accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Y.R. [Key State Laboratory of Nuclear Physics and Technology, Peking University (China)], E-mail: yrlu@pku.edu.cn; Ratzinger, U. [Institute of Applied Physics, Frankfurt University (Germany); Schlitt, B. [Gesellschaft fuer Schwerionenforschung, mbH, Darmstadt (Germany); Tiede, R. [Institute of Applied Physics, Frankfurt University (Germany)

    2007-11-21

    The RF tuning is the most important research for achieving the resonant frequency and the flatness of electric field distributions along the axis of RF accelerating structures. The six different tuning concepts and that impacts on the longitudinal field distributions have been discussed in detail combining the RF tuning process of a 1:2 modeled 20.85 MV compact IH-DTL cavity, which was designed to accelerate proton, helium, oxygen or C{sup 4+} from 400 keV/u to 7 MeV/u and used as the linear injector of 430 MeV/u synchrotron [Y.R. Lu, S. Minaev, U. Ratzinger, B. Schlitt, R.Tiede, The Compact 20MV IH-DTL for the Heidelberg Therapy Facility, in: Proceedings of the LINAC Conference, Luebeck, Germany, 2004 ; Y.R. Lu, Frankfurt University Dissertation, 2005. ] in Heidelberg Heavy Ion Cancer Therapy (HICAT). Some of tuning concepts are also suitable and effective for the tuning of RFQ and/or other RF accelerating structures. Finally good field flatness in IH-DTL cavity has been realized successfully. The experience got from the model cavity tuning benefits real power cavity tuning, which is only needed to be tuned by the plungers. The cavity had a beam commissioning successfully for the initial beam acceleration at the end of 2006.

  7. Transferability of regional permafrost disturbance susceptibility modelling using generalized linear and generalized additive models

    Science.gov (United States)

    Rudy, Ashley C. A.; Lamoureux, Scott F.; Treitz, Paul; van Ewijk, Karin Y.

    2016-07-01

    To effectively assess and mitigate risk of permafrost disturbance, disturbance-prone areas can be predicted through the application of susceptibility models. In this study we developed regional susceptibility models for permafrost disturbances using a field disturbance inventory to test the transferability of the model to a broader region in the Canadian High Arctic. Resulting maps of susceptibility were then used to explore the effect of terrain variables on the occurrence of disturbances within this region. To account for a large range of landscape characteristics, the model was calibrated using two locations: Sabine Peninsula, Melville Island, NU, and Fosheim Peninsula, Ellesmere Island, NU. Spatial patterns of disturbance were predicted with a generalized linear model (GLM) and generalized additive model (GAM), each calibrated using disturbed and randomized undisturbed locations from both locations and GIS-derived terrain predictor variables including slope, potential incoming solar radiation, wetness index, topographic position index, elevation, and distance to water. Each model was validated for the Sabine and Fosheim Peninsulas using independent data sets while the transferability of the model to an independent site was assessed at Cape Bounty, Melville Island, NU. The regional GLM and GAM validated well for both calibration sites (Sabine and Fosheim) with the area under the receiver operating curves (AUROC) > 0.79. Both models were applied directly to Cape Bounty without calibration and validated equally with AUROC's of 0.76; however, each model predicted disturbed and undisturbed samples differently. Additionally, the sensitivity of the transferred model was assessed using data sets with different sample sizes. Results indicated that models based on larger sample sizes transferred more consistently and captured the variability within the terrain attributes in the respective study areas. Terrain attributes associated with the initiation of disturbances were

  8. Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression

    Science.gov (United States)

    2016-01-01

    Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R) methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness) on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set). The original analysis of these data used a linear model (GLS) of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. Methods The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS) linear models and generalized estimating equation (GEE) models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${r}_{F}^{2}$\\end{document}rF2-test, two permutation F-tests (including GlobalAncova), and a rotation z-test (Roast). The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors) of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. Results GLS estimates are inconsistent between data

  9. Monte Carlo simulation of OLS and linear mixed model inference of phenotypic effects on gene expression

    Directory of Open Access Journals (Sweden)

    Jeffrey A. Walker

    2016-10-01

    Full Text Available Background Self-contained tests estimate and test the association between a phenotype and mean expression level in a gene set defined a priori. Many self-contained gene set analysis methods have been developed but the performance of these methods for phenotypes that are continuous rather than discrete and with multiple nuisance covariates has not been well studied. Here, I use Monte Carlo simulation to evaluate the performance of both novel and previously published (and readily available via R methods for inferring effects of a continuous predictor on mean expression in the presence of nuisance covariates. The motivating data are a high-profile dataset which was used to show opposing effects of hedonic and eudaimonic well-being (or happiness on the mean expression level of a set of genes that has been correlated with social adversity (the CTRA gene set. The original analysis of these data used a linear model (GLS of fixed effects with correlated error to infer effects of Hedonia and Eudaimonia on mean CTRA expression. Methods The standardized effects of Hedonia and Eudaimonia on CTRA gene set expression estimated by GLS were compared to estimates using multivariate (OLS linear models and generalized estimating equation (GEE models. The OLS estimates were tested using O’Brien’s OLS test, Anderson’s permutation ${r}_{F}^{2}$ r F 2 -test, two permutation F-tests (including GlobalAncova, and a rotation z-test (Roast. The GEE estimates were tested using a Wald test with robust standard errors. The performance (Type I, II, S, and M errors of all tests was investigated using a Monte Carlo simulation of data explicitly modeled on the re-analyzed dataset. Results GLS estimates are inconsistent between data sets, and, in each dataset, at least one coefficient is large and highly statistically significant. By contrast, effects estimated by OLS or GEE are very small, especially relative to the standard errors. Bootstrap and permutation GLS

  10. Solution and applications of a class of general linear variational inequalities

    Institute of Scientific and Technical Information of China (English)

    何炳生

    1996-01-01

    Many problems in mathematical programming can be described as a general linear variational inequality of the following form: find a vector u*, such thatSome iterative methods for solving a class of general linear variational inequalities have been presented. It is pointed out that the methods can be used to solve some practical extended programming problems.

  11. The generalization of some trellis properties of linear codes to group codes

    Institute of Scientific and Technical Information of China (English)

    KAN HaiBin; LI XueFei; SHEN Hong

    2009-01-01

    In this paper, we discuss some trellis properties for codes over a finite Abelian group, which are the generalization of the corresponding trellis properties for linear codes over a field. Also, we also inves-tigate difficulties when we try to generalize a property of a tail-biting trellis for a linear code over a field to a group code.

  12. Rayleigh-type Surface Quasimodes in General Linear Elasticity

    CERN Document Server

    Hansen, Sönke

    2010-01-01

    Rayleigh-type surface waves correspond to the characteristic variety, in the elliptic boundary region, of the displacement-to-traction map. In this paper, surface quasimodes are constructed for the reduced elastic wave equation, anisotropic in general, with traction-free boundary. Assuming a global variant of a condition of Barnett and Lothe, the construction is reduced to an eigenvalue problem for a selfadjoint scalar first order pseudo-differential operator on the boundary. The principal and the subprincipal symbol of this operator are computed. The formula for the subprincipal symbol seems to be new even in the isotropic case.

  13. A new linearized Crank-Nicolson mixed element scheme for the extended Fisher-Kolmogorov equation.

    Science.gov (United States)

    Wang, Jinfeng; Li, Hong; He, Siriguleng; Gao, Wei; Liu, Yang

    2013-01-01

    We present a new mixed finite element method for solving the extended Fisher-Kolmogorov (EFK) equation. We first decompose the EFK equation as the two second-order equations, then deal with a second-order equation employing finite element method, and handle the other second-order equation using a new mixed finite element method. In the new mixed finite element method, the gradient ∇u belongs to the weaker (L²(Ω))² space taking the place of the classical H(div; Ω) space. We prove some a priori bounds for the solution for semidiscrete scheme and derive a fully discrete mixed scheme based on a linearized Crank-Nicolson method. At the same time, we get the optimal a priori error estimates in L² and H¹-norm for both the scalar unknown u and the diffusion term w = -Δu and a priori error estimates in (L²)²-norm for its gradient χ = ∇u for both semi-discrete and fully discrete schemes.

  14. Linear matrix inequality approach for synchronization control of fuzzy cellular neural networks with mixed time delays

    Institute of Scientific and Technical Information of China (English)

    P. Balasubramaniam; M. Kalpana; R. Rakkiyappan

    2012-01-01

    Fuzzy cellular neural networks (FCNNs) are special kinds of cellular neural networks (CNNs).Each cell in an FCNN contains fuzzy operating abilities.The entire network is governed by cellular computing laws.The design of FCNNs is based on fuzzy local rules.In this paper,a linear matrix inequality (LMI) approach for synchronization control of FCNNs with mixed delays is investigated.Mixed delays include discrete time-varying delays and unbounded distributed delays.A dynamic control scheme is proposed to achieve the synchronization between a drive network and a response network.By constructing the Lyapunov-Krasovskii functional which contains a triple-integral term and the free-weighting matrices method an improved delay-dependent stability criterion is derived in terms of LMIs.The controller can be easily obtained by solving the derived LMIs.A numerical example and its simulations are presented to illustrate the effectiveness of the proposed method.

  15. Evaluation of structure specification in linear mixed models for modeling the spatial effects in tree height-diamater relationships

    Directory of Open Access Journals (Sweden)

    Junfeng Lu

    2013-07-01

    Full Text Available In recent years, linear mixed models (LMM have become more popular to deal with spatial effects in forestry and ecological data. In this study, different structure specifications of linear mixed model were applied to model tree height-diameter relationships, including LMM with random blocks only (LMM-block, LMM with spatial covariance only (LMM-covariance, and the combination of the last two (LMM-block-covariance. Further, the between-group heterogeneous variances were incorporated into LMM-covariance and LMM-block-covariance. The results indicated that, in general, LMM-covariance significantly reduced spatial autocorrelation in model residuals, while LMM-block was effective in dealing with spatial heterogeneity. LMM-block treated the blocks as random effects and avoided the estimation of parameters of the variogram model. Thus, it produced better model predictions than LMM-covariance. LMM-block-covariance took both block effects and spatial covariance into account, and significantly improve model fitting. However, it did not produce better model predictions due to the increase of model complexity and estimation of the local variogram within each block. 

  16. The left invariant metric in the general linear group

    CERN Document Server

    Andruchow, Esteban; Recht, Lazaro; Varela, Alejandro

    2011-01-01

    Left invariant metrics induced by the p-norms of the trace in the matrix algebra are studied on the general lineal group. By means of the Euler-Lagrange equations, existence and uniqueness of extremal paths for the length functional are established, and regularity properties of these extremal paths are obtained. Minimizing paths in the group are shown to have a velocity with constant singular values and multiplicity. In several special cases, these geodesic paths are computed explicitly. In particular the Riemannian geodesics, corresponding to the case p=2, are characterized as the product of two one-parameter groups. It is also shown that geodesics are one-parameter groups if and only if the initial velocity is a normal matrix. These results are further extended to the context of compact operators with p-summable spectrum, where a differential equation for the spectral projections of the velocity vector of an extremal path is obtained.

  17. Item Response Theory Using Hierarchical Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    Hamdollah Ravand

    2015-03-01

    Full Text Available Multilevel models (MLMs are flexible in that they can be employed to obtain item and person parameters, test for differential item functioning (DIF and capture both local item and person dependence. Papers on the MLM analysis of item response data have focused mostly on theoretical issues where applications have been add-ons to simulation studies with a methodological focus. Although the methodological direction was necessary as a first step to show how MLMs can be utilized and extended to model item response data, the emphasis needs to be shifted towards providing evidence on how applications of MLMs in educational testing can provide the benefits that have been promised. The present study uses foreign language reading comprehension data to illustrate application of hierarchical generalized models to estimate person and item parameters, differential item functioning (DIF, and local person dependence in a three-level model.

  18. Inferences in Linear Mixed Models with Skew-normal Random Eff ects

    Institute of Scientific and Technical Information of China (English)

    Ren Dao YE; Tong Hui WANG

    2015-01-01

    For the linear mixed model with skew-normal random eff ects, this paper gives the density function, moment generating function and independence conditions. The noncentral skew chi-square distribution is defined and its density function is shown. The necessary and suffi cient conditions under which a quadratic form is distributed as noncentral skew chi-square distribution are obtained. Also, a version of Cochran’s theorem is given, which modifies the result of Wang et al. (2009) and is used to set up exact tests for fixed eff ects and variance components of the proposed model. For illustration, our main results are applied to a real data problem.

  19. An overview of solution methods for multi-objective mixed integer linear programming programs

    DEFF Research Database (Denmark)

    Andersen, Kim Allan; Stidsen, Thomas Riis

    Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...

  20. Linear polymer aqueous solutions in soft lubrication:From boundary to mixed lubrication

    Institute of Scientific and Technical Information of China (English)

    LIU; ShuHai; TAN; GuiBin; WANG; DeGuo

    2013-01-01

    In order to better understand linear polymer aqueous solutions in soft lubrication from boundary to mixed lubrication,poly(ethylene glycol) and sodium hyaluronateare used as model polymers were investigated by using UMT-2 tribometer with the ball-on-disk mode. The relationship between the master Stribeck curves of the polymer aqueous solutions and the influence factors were investigated. Experimental results indicated that soft lubrication is determined by lubricant rheological properties and surface-lubricant interactions, e.g., wetting behavior of polymer aqueous solution on tribological surfaces.

  1. A mixed relaxed singular maximum principle for linear SDEs with random coefficients

    CERN Document Server

    Andersson, Daniel

    2008-01-01

    We study singular stochastic control of a two dimensional stochastic differential equation, where the first component is linear with random and unbounded coefficients. We derive existence of an optimal relaxed control and necessary conditions for optimality in the form of a mixed relaxed-singular maximum principle in a global form. A motivating example is given in the form of an optimal investment and consumption problem with transaction costs, where we consider a portfolio with a continuum of bonds and where the portfolio weights are modeled as measure-valued processes on the set of times to maturity.

  2. An overview of solution methods for multi-objective mixed integer linear programming programs

    DEFF Research Database (Denmark)

    Andersen, Kim Allan; Stidsen, Thomas Riis

    Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...

  3. The Time Discontinuous H1-Galerkin Mixed Finite Element Method for Linear Sobolev Equations

    Directory of Open Access Journals (Sweden)

    Hong Yu

    2015-01-01

    Full Text Available We combine the H1-Galerkin mixed finite element method with the time discontinuous Galerkin method to approximate linear Sobolev equations. The advantages of these two methods are fully utilized. The approximate schemes are established to get the approximate solutions by a piecewise polynomial of degree at most q-1 with the time variable. The existence and uniqueness of the solutions are proved, and the optimal H1-norm error estimates are derived. We get high accuracy for both the space and time variables.

  4. Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression

    Directory of Open Access Journals (Sweden)

    Marco Geraci

    2014-05-01

    Full Text Available Inference in quantile analysis has received considerable attention in the recent years. Linear quantile mixed models (Geraci and Bottai 2014 represent a ?exible statistical tool to analyze data from sampling designs such as multilevel, spatial, panel or longitudinal, which induce some form of clustering. In this paper, I will show how to estimate conditional quantile functions with random e?ects using the R package lqmm. Modeling, estimation and inference are discussed in detail using a real data example. A thorough description of the optimization algorithms is also provided.

  5. Mixed finite element methods for linear elasticity with weakly imposed symmetry

    Science.gov (United States)

    Arnold, Douglas N.; Falk, Richard S.; Winther, Ragnar

    2007-12-01

    In this paper, we construct new finite element methods for the approximation of the equations of linear elasticity in three space dimensions that produce direct approximations to both stresses and displacements. The methods are based on a modified form of the Hellinger-Reissner variational principle that only weakly imposes the symmetry condition on the stresses. Although this approach has been previously used by a number of authors, a key new ingredient here is a constructive derivation of the elasticity complex starting from the de Rham complex. By mimicking this construction in the discrete case, we derive new mixed finite elements for elasticity in a systematic manner from known discretizations of the de Rham complex. These elements appear to be simpler than the ones previously derived. For example, we construct stable discretizations which use only piecewise linear elements to approximate the stress field and piecewise constant functions to approximate the displacement field.

  6. Optimal composite scores for longitudinal clinical trials under the linear mixed effects model.

    Science.gov (United States)

    Ard, M Colin; Raghavan, Nandini; Edland, Steven D

    2015-01-01

    Clinical trials of chronic, progressive conditions use rate of change on continuous measures as the primary outcome measure, with slowing of progression on the measure as evidence of clinical efficacy. For clinical trials with a single prespecified primary endpoint, it is important to choose an endpoint with the best signal-to-noise properties to optimize statistical power to detect a treatment effect. Composite endpoints composed of a linear weighted average of candidate outcome measures have also been proposed. Composites constructed as simple sums or averages of component tests, as well as composites constructed using weights derived from more sophisticated approaches, can be suboptimal, in some cases performing worse than individual outcome measures. We extend recent research on the construction of efficient linearly weighted composites by establishing the often overlooked connection between trial design and composite performance under linear mixed effects model assumptions and derive a formula for calculating composites that are optimal for longitudinal clinical trials of known, arbitrary design. Using data from a completed trial, we provide example calculations showing that the optimally weighted linear combination of scales can improve the efficiency of trials by almost 20% compared with the most efficient of the individual component scales. Additional simulations and analytical results demonstrate the potential losses in efficiency that can result from alternative published approaches to composite construction and explore the impact of weight estimation on composite performance.

  7. Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

    KAUST Repository

    Canepa, Edward S.

    2013-09-01

    Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.

  8. Spoofing cyber attack detection in probe-based traffic monitoring systems using mixed integer linear programming

    KAUST Repository

    Canepa, Edward S.

    2013-01-01

    Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.

  9. Stability Criterion of Linear Stochastic Systems Subject to Mixed H2/Passivity Performance

    Directory of Open Access Journals (Sweden)

    Cheung-Chieh Ku

    2015-01-01

    Full Text Available The H2 control scheme and passivity theory are applied to investigate the stability criterion of continuous-time linear stochastic system subject to mixed performance. Based on the stochastic differential equation, the stochastic behaviors can be described as multiplicative noise terms. For the considered system, the H2 control scheme is applied to deal with the problem on minimizing output energy. And the asymptotical stability of the system can be guaranteed under desired initial conditions. Besides, the passivity theory is employed to constrain the effect of external disturbance on the system. Moreover, the Itô formula and Lyapunov function are used to derive the sufficient conditions which are converted into linear matrix inequality (LMI form for applying convex optimization algorithm. Via solving the sufficient conditions, the state feedback controller can be established such that the asymptotical stability and mixed performance of the system are achieved in the mean square. Finally, the synchronous generator system is used to verify the effectiveness and applicability of the proposed design method.

  10. Generalized theory of mixed pole machines with a general rotor configuration

    Directory of Open Access Journals (Sweden)

    Ayman S. Abdel-khalik

    2013-03-01

    Full Text Available This paper introduces a generalized theory for the operation of mixed pole machines (MPMs. The MPM has two stator windings, namely the main winding with pole pairs P1 and the control winding with pole pairs P2. The MPM has shown promise in the field of adjustable speed drives for large machines and in the field of wind energy electrical generation. The operation of MPM relies on the interaction between the two fields produced by the two stator windings through the intermediate action of a specially designed rotor (nested-cage or reluctance rotor. The machine theory is described from a physical aspect rather than mathematical derivations. A simple representation is also presented, from which the machine d–q model can be readily deduced. The effect of mechanical loading on the relative positions of the machine fields is also presented.

  11. A Neural Network Based Hybrid Mixture Model to Extract Information from Non-linear Mixed Pixels

    Directory of Open Access Journals (Sweden)

    Uttam Kumar

    2012-09-01

    Full Text Available Signals acquired by sensors in the real world are non-linear combinations, requiring non-linear mixture models to describe the resultant mixture spectra for the endmember’s (pure pixel’s distribution. This communication discusses inferring class fraction through a novel hybrid mixture model (HMM. HMM is a three-step process, where the endmembers are first derived from the images themselves using the N-FINDR algorithm. These endmembers are used by the linear mixture model (LMM in the second step that provides an abundance estimation in a linear fashion. Finally, the abundance values along with the training samples representing the actual ground proportions are fed into neural network based multi-layer perceptron (MLP architecture as input to train the neurons. The neural output further refines the abundance estimates to account for the non-linear nature of the mixing classes of interest. HMM is first implemented and validated on simulated hyper spectral data of 200 bands and subsequently on real time MODIS data with a spatial resolution of 250 m. The results on computer simulated data show that the method gives acceptable results for unmixing pixels with an overall RMSE of 0.0089 ± 0.0022 with LMM and 0.0030 ± 0.0001 with the HMM when compared to actual class proportions. The unmixed MODIS images showed overall RMSE with HMM as 0.0191 ± 0.022 as compared to the LMM output considered alone that had an overall RMSE of 0.2005 ± 0.41, indicating that individual class abundances obtained from HMM are very close to the real observations.

  12. Ability of non-linear mixed models to predict growth in laying hens

    Directory of Open Access Journals (Sweden)

    Luis Fernando Galeano-Vasco

    2014-11-01

    Full Text Available In this study, the Von Bertalanffy, Richards, Gompertz, Brody, and Logistics non-linear mixed regression models were compared for their ability to estimate the growth curve in commercial laying hens. Data were obtained from 100 Lohmann LSL layers. The animals were identified and then weighed weekly from day 20 after hatch until they were 553 days of age. All the nonlinear models used were transformed into mixed models by the inclusion of random parameters. Accuracy of the models was determined by the Akaike and Bayesian information criteria (AIC and BIC, respectively, and the correlation values. According to AIC, BIC, and correlation values, the best fit for modeling the growth curve of the birds was obtained with Gompertz, followed by Richards, and then by Von Bertalanffy models. The Brody and Logistic models did not fit the data. The Gompertz nonlinear mixed model showed the best goodness of fit for the data set, and is considered the model of choice to describe and predict the growth curve of Lohmann LSL commercial layers at the production system of University of Antioquia.

  13. Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

    Directory of Open Access Journals (Sweden)

    H Kazemipoor

    2012-04-01

    Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.

  14. Generalized Hyers-Ulam Stability of a General Mixed Additive-cubic Functional Equation in Quasi-Banach Spaces

    Institute of Scientific and Technical Information of China (English)

    Tian Zhou XU; John Michael RASSIAS; Wan Xin XU

    2012-01-01

    In this paper,we establish a general solution and the generalized Hyers-Ulam-Rassias stability of the following general mixed additive-cubic functional equation f(kx + y) + f(kx - y) =kf(x + y) + kf(x - y) + 2f(kx) - 2kf(x)in the quasi-Banach spaces.

  15. L{sup P}-posteriori error analysis of mixed methods for linear and quasilinear elliptic problems

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Z. [Texas A& M Univ., College Station, TX (United States)

    1995-12-31

    We consider mixed finite element methods for the approximation of linear and quasilinear second-order elliptic problems. A class of postprocessing methods for improving mixed finite element solutions is analyzed. In particular, error estimates in L{sup p}, 1{<=}p{<=}{infinity}, are given. These postprocessing methods are applicable to an the existing mixed methods, and can be easily implemented. Furthermore, they are local and thus fully parallelizable.

  16. Impacto não Linear do Marketing Mix no Desempenho em Vendas de Marcas

    Directory of Open Access Journals (Sweden)

    Rafael Barreiros Porto

    2015-01-01

    Full Text Available O padrão de impacto que as atividades de marketingexercem nas vendas não tem sido evidenciado na literatura. Muitas pesquisas adotam perspectivas lineares restritas, desconsiderando as evidências empíricas. Este trabalho investigou o impacto não linear do marketingmixno volume em vendas e no volume de consumidores e de compra por consumidor. Realizou-se um estudo longitudinal em painel de marcas e de consumidores simultâneos. Analisaram-se 121 marcas durante 13 meses, com 793 compras/mês feitas pelos consumidores por meio de três equações de estimativas generalizadas. Os resultados apontam que o marketing mix, em especial brandinge precificação, impacta fortemente todas as dependentes em formato não linear, com bons ajustes dos parâmetros. Oefeito conjunto gera economias de escala para as marcas, enquanto, para cada consumidor, o efeito conjunto estimula-o a adquirir maiores quantidades gradativamente. A pesquisa demonstra oito padrões impactantes do marketingmixsobre os indicadores investigados, com alterações de sua ordem e de seu peso para marcas e consumidores.

  17. On the General Taylor Theorem and its Applications in Solving Non—linear Problems

    Institute of Scientific and Technical Information of China (English)

    ShiJunLIAO

    1997-01-01

    In this paper,we propose a general Taylor series and prove a general Taylor theorem and then simply give some applications of it in solving non-linear differential equations.The general Taylor series is a family of power series which contains the classical Taylor series in logic.Moreover,it can be valid in much larger regions.

  18. Generalized functional linear models for gene-based case-control association studies.

    Science.gov (United States)

    Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao

    2014-11-01

    By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses.

  19. An efficient method for generalized linear multiplicative programming problem with multiplicative constraints

    OpenAIRE

    Zhao, Yingfeng; Liu, Sanyang

    2016-01-01

    We present a practical branch and bound algorithm for globally solving generalized linear multiplicative programming problem with multiplicative constraints. To solve the problem, a relaxation programming problem which is equivalent to a linear programming is proposed by utilizing a new two-phase relaxation technique. In the algorithm, lower and upper bounds are simultaneously obtained by solving some linear relaxation programming problems. Global convergence has been proved and results of so...

  20. Generalized Virial Theorem for Mixed State When Hamiltonians Include Coordinate-Momentum Couplings

    Institute of Scientific and Technical Information of China (English)

    YUAN Hao; WANG Min; HE Qin; HU Xiao-Yuan; HOU Kui; HAN Lian-Fang; SHI Shou-Hua

    2008-01-01

    The generalized Virial theorem for mixed state, derived from the generalized Hellmann-Feynman theorem, only applies to Hamiltonians in which potential of coordinates is separate from momentum energy term. In this paper we discuss Virial theorem for mixed state for some Hamiltonians with coordinate-momentum couplings in order to know their contributions to internal energy.

  1. Optical nonlinear response function with linear and diagonal quadratic electron-vibration coupling in mixed quantum-classical systems.

    Science.gov (United States)

    Toutounji, Mohamad

    2005-03-22

    While an optical linear response function of linearly and quadratically coupled mixed quantum-classical condensed-phase systems was derived by Toutounji [J. Chem. Phys. 121, 2228 (2004)], the corresponding analytical optical line shape is derived. The respective nonlinear correlation functions are also derived. Model calculations involving photon-echo, pump-probe, and hole-burning signals of model systems with both linear and quadratic coupling are provided. Hole-burning formula of Hayes-Small is compared to that of Mukamel in mixed quantum-classical systems.

  2. ORDER RESULTS OF GENERAL LINEAR METHODS FOR MULTIPLY STIFF SINGULAR PERTURBATION PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    Si-qing Gan; Geng Sun

    2002-01-01

    In this paper we analyze the error behavior of general linear methods applied to some classes of one-parameter multiply stiff singularly perturbed problems. We obtain the global error estimate of algebraically and diagonally stable general linear methods. The main result of this paper can be viewed as an extension of that obtained by Xiao [13] for the case of Runge-Kutta methods.

  3. Mixed-Mode Oscillations in a piecewise linear system with multiple time scale coupling

    Science.gov (United States)

    Fernández-García, S.; Krupa, M.; Clément, F.

    2016-10-01

    In this work, we analyze a four dimensional slow-fast piecewise linear system with three time scales presenting Mixed-Mode Oscillations. The system possesses an attractive limit cycle along which oscillations of three different amplitudes and frequencies can appear, namely, small oscillations, pulses (medium amplitude) and one surge (largest amplitude). In addition to proving the existence and attractiveness of the limit cycle, we focus our attention on the canard phenomena underlying the changes in the number of small oscillations and pulses. We analyze locally the existence of secondary canards leading to the addition or subtraction of one small oscillation and describe how this change is globally compensated for or not with the addition or subtraction of one pulse.

  4. Mixed-mode implementation of PETSc for scalable linear algebra on multi-core processors

    CERN Document Server

    Weiland, Michele; Gorman, Gerard; Kramer, Stephan; Parsons, Mark; Southern, James

    2012-01-01

    With multi-core processors a ubiquitous building block of modern supercomputers, it is now past time to enable applications to embrace these developments in processor design. To achieve exascale performance, applications will need ways of exploiting the new levels of parallelism that are exposed in modern high-performance computers. A typical approach to this is to use shared-memory programming techniques to best exploit multi-core nodes along with inter-node message passing. In this paper, we describe the addition of OpenMP threaded functionality to the PETSc library. We highlight some issues that hinder good performance of threaded applications on modern processors and describe how to negate them. The OpenMP branch of PETSc was benchmarked using matrices extracted from the Fluidity CFD application, which uses the library as its linear solver engine. The overall performance of the mixed-mode implementation is shown to be superior to that of the pure-MPI version.

  5. Mixed-Integer Linear Programming Models for Teaching Assistant Assignment and Extensions

    Directory of Open Access Journals (Sweden)

    Xiaobo Qu

    2017-01-01

    Full Text Available In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant’s teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a time-consuming process, does not need to be carried out in a manual manner. We have further presented a number of extensions that capture more practical considerations. Extensive numerical experiments show that the optimization models can be solved by an off-the-shelf solver and used by departments in universities.

  6. Measurement of the Beam Longitudinal Profile in a Storage Ring by Non-Linear Laser Mixing

    Science.gov (United States)

    Beche, J.-F.; Byrd, J.; De Santis, S.; Denes, P.; Placidi, M.; Turner, W.; Zolotorev, M.

    2004-11-01

    We report on the development of a new technique for the measurement of the longitudinal beam profile in storage rings. This technique, which has been successfully demonstrated at the Advanced Light Source, mixes the synchrotron radiation with the light from a mode-locked solid-state laser oscillator in a non-linear crystal. The up-converted radiation is then detected with a photomultiplier and processed to extract, store, and display the required information. The available choices of laser repetition frequency, pulse width, and phase modulation give a wide range of options for matching the bunch configuration of a particular storage ring. Besides the dynamic measurement of the longitudinal profile of each bunch, the instrument can monitor the evolution of the bunch tails, the presence of un trapped particles, and their diffusion into nominally empty RF buckets ("ghost bunches").

  7. Measurement of the beam longitudinal profile in a storage ring bynon-linear laser mixing

    Energy Technology Data Exchange (ETDEWEB)

    Beche, J.-F.; Byrd, J.; De Santis, S.; Denes, P.; Placidi, M.; Turner, W.; Zolotorev, M.

    2004-05-03

    We report on the development of a new technique for the measurement of the longitudinal beam profile in storage rings. This technique, which has been successfully demonstrated at the Advanced Light Source, mixes the synchrotron radiation with the light from a mode-locked solid state laser oscillator in a non-linear crystal. The up-converted radiation is then detected with a photomultiplier and processed to extract, store, and display the required information. The available choices of laser repetition frequency, pulse width, and phase modulation give a wide range of options for matching the bunch configuration of a particular storage ring. Besides the dynamic measurement of the longitudinal profile of each bunch, the instrument can monitor the evolution of the bunch tails, the presence of untrapped particles and their diffusion into nominally empty RF buckets (''ghostbunches'').

  8. Modeling vibrational resonance in linear hydrocarbon chain with a mixed quantum-classical method.

    Science.gov (United States)

    Gelman, David; Schwartz, Steven D

    2009-04-07

    The quantum dynamics of a vibrational excitation in a linear hydrocarbon model system is studied with a new mixed quantum-classical method. The method is suited to treat many-body systems consisting of a low dimensional quantum primary part coupled to a classical bath. The dynamics of the primary part is governed by the quantum corrected propagator, with the corrections defined in terms of matrix elements of zeroth order propagators. The corrections are taken to the classical limit by introducing the frozen Gaussian approximation for the bath degrees of freedom. The ability of the method to describe dynamics of multidimensional systems has been tested. The results obtained by the method have been compared to previous quantum simulations performed with the quasiadiabatic path integral method.

  9. FC-TLBO: fully constrained meta-heuristic algorithm for abundance estimation using linear mixing model

    Indian Academy of Sciences (India)

    OMPRAKASH TEMBHURNE; DEEPTI SHRIMANKAR

    2017-07-01

    A study of abundance estimation has vital importance in spectral unmixing of hyperspectral image. Recently, various methods have been proposed for spectral unmixing to achieve higher performance using an evolutionary approach. However, these methods are based on unconstrained optimisation problems. Theirperformance was also based on proper tuning parameters. We have proposed a new non-parametric algorithm using teaching-learning-based optimisation technique with an inbuilt constraints maintenance mechanism using the linear mixing model. In this approach, the unmixing problem is transformed into a combinatorial optimisation problem by introducing abundance sum to one constraint and abundance non-negative constraint. A comparative analysis of the proposed algorithm is conducted with other two state-of-the-art algorithms.Experimental results in known and unknown environments with varying signal-to-noise ratio on simulated and real hyper spectral data demonstrate that the proposed method outperforms the other methods.

  10. Reliability based design optimization of concrete mix proportions using generalized ridge regression model

    Directory of Open Access Journals (Sweden)

    Rachna Aggarwal

    2014-12-01

    Full Text Available This paper presents Reliability Based Design Optimization (RBDO model to deal with uncertainties involved in concrete mix design process. The optimization problem is formulated in such a way that probabilistic concrete mix input parameters showing random characteristics are determined by minimizing the cost of concrete subjected to concrete compressive strength constraint for a given target reliability.  Linear and quadratic models based on Ordinary Least Square Regression (OLSR, Traditional Ridge Regression (TRR and Generalized Ridge Regression (GRR techniques have been explored to select the best model to explicitly represent compressive strength of concrete. The RBDO model is solved by Sequential Optimization and Reliability Assessment (SORA method using fully quadratic GRR model. Optimization results for a wide range of target compressive strength and reliability levels of 0.90, 0.95 and 0.99 have been reported. Also, safety factor based Deterministic Design Optimization (DDO designs for each case are obtained. It has been observed that deterministic optimal designs are cost effective but proposed RBDO model gives improved design performance.

  11. Axial displacement of external and internal implant-abutment connection evaluated by linear mixed model analysis.

    Science.gov (United States)

    Seol, Hyon-Woo; Heo, Seong-Joo; Koak, Jai-Young; Kim, Seong-Kyun; Kim, Shin-Koo

    2015-01-01

    To analyze the axial displacement of external and internal implant-abutment connection after cyclic loading. Three groups of external abutments (Ext group), an internal tapered one-piece-type abutment (Int-1 group), and an internal tapered two-piece-type abutment (Int-2 group) were prepared. Cyclic loading was applied to implant-abutment assemblies at 150 N with a frequency of 3 Hz. The amount of axial displacement, the Periotest values (PTVs), and the removal torque values(RTVs) were measured. Both a repeated measures analysis of variance and pattern analysis based on the linear mixed model were used for statistical analysis. Scanning electron microscopy (SEM) was used to evaluate the surface of the implant-abutment connection. The mean axial displacements after 1,000,000 cycles were 0.6 μm in the Ext group, 3.7 μm in the Int-1 group, and 9.0 μm in the Int-2 group. Pattern analysis revealed a breakpoint at 171 cycles. The Ext group showed no declining pattern, and the Int-1 group showed no declining pattern after the breakpoint (171 cycles). However, the Int-2 group experienced continuous axial displacement. After cyclic loading, the PTV decreased in the Int-2 group, and the RTV decreased in all groups. SEM imaging revealed surface wear in all groups. Axial displacement and surface wear occurred in all groups. The PTVs remained stable, but the RTVs decreased after cyclic loading. Based on linear mixed model analysis, the Ext and Int-1 groups' axial displacements plateaued after little cyclic loading. The Int-2 group's rate of axial displacement slowed after 100,000 cycles.

  12. Generating synthetic wave climates for coastal modelling: a linear mixed modelling approach

    Science.gov (United States)

    Thomas, C.; Lark, R. M.

    2013-12-01

    Numerical coastline morphological evolution models require wave climate properties to drive morphological change through time. Wave climate properties (typically wave height, period and direction) may be temporally fixed, culled from real wave buoy data, or allowed to vary in some way defined by a Gaussian or other pdf. However, to examine sensitivity of coastline morphologies to wave climate change, it seems desirable to be able to modify wave climate time series from a current to some new state along a trajectory, but in a way consistent with, or initially conditioned by, the properties of existing data, or to generate fully synthetic data sets with realistic time series properties. For example, mean or significant wave height time series may have underlying periodicities, as revealed in numerous analyses of wave data. Our motivation is to develop a simple methodology to generate synthetic wave climate time series that can change in some stochastic way through time. We wish to use such time series in a coastline evolution model to test sensitivities of coastal landforms to changes in wave climate over decadal and centennial scales. We have worked initially on time series of significant wave height, based on data from a Waverider III buoy located off the coast of Yorkshire, England. The statistical framework for the simulation is the linear mixed model. The target variable, perhaps after transformation (Box-Cox), is modelled as a multivariate Gaussian, the mean modelled as a function of a fixed effect, and two random components, one of which is independently and identically distributed (iid) and the second of which is temporally correlated. The model was fitted to the data by likelihood methods. We considered the option of a periodic mean, the period either fixed (e.g. at 12 months) or estimated from the data. We considered two possible correlation structures for the second random effect. In one the correlation decays exponentially with time. In the second

  13. Mixing height determination using remote sensing systems. General remarks

    Energy Technology Data Exchange (ETDEWEB)

    Beyrich, F. [BTU Cottbus, LS Umweltmeteorologie, Cottbus (Germany)

    1997-10-01

    Remote sensing systems can be considered today as a real alternative to classical soundings with respect to the MH (mixing height) determination. They have the basic advantage to allow continuous monitoring of the ABL (atmospheric boundary layer). Some technical issues which limit their operational use at present should be solved in the near future (frequency allocation, eye safety, costs). Taking into account specific operating conditions and the formulated-above requirements of a sounding system to be used for MH determination it becomes obvious that none of the available systems meets all of them, i.e., the `Mixing height-meter` does not exist. Therefore, reliable MH determination under a wide variety of conditions can be achieved only by integrating different instruments into a complex sounding system. The S-profiles provide a suitable data base for MH estimation from all types of remote sensing instruments. The criteria to deduce MH-values from these profiles should consider the structure type and the evolution stage of the ABL as well as the shape of the profiles. A certain kind of harmonization concerning these criteria should be achieved. MH values derived automatically from remote sensing data appear to be not yet reliable enough for direct operational use, they should be in any case critically examined by a trained analyst. Contemporary mathematical methods (wavelet transforms, fuzzy logics) are supposed to allow considerable progress in this field in the near future. (au) 19 refs.

  14. Finite element model for linear-elastic mixed mode loading using adaptive mesh strategy

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    An adaptive mesh finite element model has been developed to predict the crack propagation direction as well as to calculate the stress intensity factors (SIFs), under linear-elastic assumption for mixed mode loading application. The finite element mesh is generated using the advancing front method. In order to suit the requirements of the fracture analysis, the generation of the background mesh and the construction of singular elements have been added to the developed program. The adaptive remeshing process is carried out based on the posteriori stress error norm scheme to obtain an optimal mesh. Previous works of the authors have proposed techniques for adaptive mesh generation of 2D cracked models. Facilitated by the singular elements, the displacement extrapolation technique is employed to calculate the SIF. The fracture is modeled by the splitting node approach and the trajectory follows the successive linear extensions of each crack increment. The SIFs values for two different case studies were estimated and validated by direct comparisons with other researchers work.

  15. Linear Optimization Techniques for Product-Mix of Paints Production in Nigeria

    Directory of Open Access Journals (Sweden)

    Sulaimon Olanrewaju Adebiyi

    2014-02-01

    Full Text Available Many paint producers in Nigeria do not lend themselves to flexible production process which is important for them to manage the use of resources for effective optimal production. These goals can be achieved through the application of optimization models in their resources allocation and utilisation. This research focuses on linear optimization for achieving product- mix optimization in terms of the product identification and the right quantity in paint production in Nigeria for better profit and optimum firm performance. The computational experiments in this research contains data and information on the units item costs, unit contribution margin, maximum resources capacity, individual products absorption rate and other constraints that are particular to each of the five products produced in the company employed as case study. In data analysis, linear programming model was employed with the aid LINDO 11 software to analyse the data. The result has showed that only two out of the five products under consideration are profitable. It also revealed the rate to which the company needs to reduce cost incurred on the three other products before making them profitable for production.

  16. Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

    Science.gov (United States)

    Baran, Richard; Northen, Trent R

    2013-10-15

    Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

  17. Univariate and multivariate general linear models theory and applications with SAS

    CERN Document Server

    Kim, Kevin

    2006-01-01

    Reviewing the theory of the general linear model (GLM) using a general framework, Univariate and Multivariate General Linear Models: Theory and Applications with SAS, Second Edition presents analyses of simple and complex models, both univariate and multivariate, that employ data sets from a variety of disciplines, such as the social and behavioral sciences.With revised examples that include options available using SAS 9.0, this expanded edition divides theory from applications within each chapter. Following an overview of the GLM, the book introduces unrestricted GLMs to analyze multiple regr

  18. Power and sample size for the S:T repeated measures design combined with a linear mixed-effects model allowing for missing data.

    Science.gov (United States)

    Tango, Toshiro

    2017-02-13

    Tango (Biostatistics 2016) proposed a new repeated measures design called the S:T repeated measures design, combined with generalized linear mixed-effects models and sample size calculations for a test of the average treatment effect that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size compared with the simple pre-post design. In this article, we present formulas for calculating power and sample sizes for a test of the average treatment effect allowing for missing data within the framework of the S:T repeated measures design with a continuous response variable combined with a linear mixed-effects model. Examples are provided to illustrate the use of these formulas.

  19. Predicting infectivity of Arbuscular Mycorrhizal fungi from soil variables using Generalized Additive Models and Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    IRNANDA AIKO FIFI DJUUNA

    2010-07-01

    Full Text Available Djuuna IAF, Abbott LK, Van Niel K (2010 Predicting infectivity of Arbuscular Mycorrhizal fungi from soil variables using Generalized Additive Models and Generalized Linear Models. Biodiversitas 11: 145-150. The objective of this study was to predict the infectivity of arbuscular mycorrhizal fungi (AM fungi, from field soil based on soil properties and land use history using generalized additive models (GAMs and generalized linear models (GLMs. A total of 291 soil samples from a farm in Western Australia near Wickepin were collected and used in this study. Nine soil properties, including elevation, pH, EC, total C, total N, P, K, microbial biomass carbon, and soil texture, and land use history of the farm were used as independent variables, while the percentage of root length colonized (%RLC was used as the dependent variable. GAMs parameterized for the percent of root length colonized suggested skewed quadratic responses to soil pH and microbial biomass carbon; cubic responses to elevation and soil K; and linear responses to soil P, EC and total C. The strength of the relationship between percent root length colonized by AM fungi and environmental variables showed that only elevation, total C and microbial biomass carbon had strong relationships. In general, GAMs and GLMs models confirmed the strong relationship between infectivity of AM fungi (assessed in a glasshouse bioassay for soil collected in summer prior to the first rain of the season and soil properties.

  20. Asymptotic normality and strong consistency of maximum quasi-likelihood estimates in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    YIN; Changming; ZHAO; Lincheng; WEI; Chengdong

    2006-01-01

    In a generalized linear model with q × 1 responses, the bounded and fixed (or adaptive) p × q regressors Zi and the general link function, under the most general assumption on the minimum eigenvalue of ∑ni=1 ZiZ'i, the moment condition on responses as weak as possible and the other mild regular conditions, we prove that the maximum quasi-likelihood estimates for the regression parameter vector are asymptotically normal and strongly consistent.

  1. Optimization of end-members used in multiple linear regression geochemical mixing models

    Science.gov (United States)

    Dunlea, Ann G.; Murray, Richard W.

    2015-11-01

    Tracking marine sediment provenance (e.g., of dust, ash, hydrothermal material, etc.) provides insight into contemporary ocean processes and helps construct paleoceanographic records. In a simple system with only a few end-members that can be easily quantified by a unique chemical or isotopic signal, chemical ratios and normative calculations can help quantify the flux of sediment from the few sources. In a more complex system (e.g., each element comes from multiple sources), more sophisticated mixing models are required. MATLAB codes published in Pisias et al. solidified the foundation for application of a Constrained Least Squares (CLS) multiple linear regression technique that can use many elements and several end-members in a mixing model. However, rigorous sensitivity testing to check the robustness of the CLS model is time and labor intensive. MATLAB codes provided in this paper reduce the time and labor involved and facilitate finding a robust and stable CLS model. By quickly comparing the goodness of fit between thousands of different end-member combinations, users are able to identify trends in the results that reveal the CLS solution uniqueness and the end-member composition precision required for a good fit. Users can also rapidly check that they have the appropriate number and type of end-members in their model. In the end, these codes improve the user's confidence that the final CLS model(s) they select are the most reliable solutions. These advantages are demonstrated by application of the codes in two case studies of well-studied datasets (Nazca Plate and South Pacific Gyre).

  2. GENERAL CENTRAL PATH AND THE LARGEST STEP GENERAL CENTRAL PATH FOLLOWING ALGORITHM FOR LINEAR PROGRAMMING

    Institute of Scientific and Technical Information of China (English)

    艾文宝; 张可村

    2001-01-01

    In this paper, we propose a general path following method, in which the starting point can be any feasible interior pair and each iteration uses a step with the largest possible reduction in duality gap. The algorithm maintains the O ( nL) ineration complexity. It enjoys quadratic convergence if the optimal vertex is nondegenerate.

  3. Meta-analysis of Complex Diseases at Gene Level with Generalized Functional Linear Models.

    Science.gov (United States)

    Fan, Ruzong; Wang, Yifan; Chiu, Chi-Yang; Chen, Wei; Ren, Haobo; Li, Yun; Boehnke, Michael; Amos, Christopher I; Moore, Jason H; Xiong, Momiao

    2016-02-01

    We developed generalized functional linear models (GFLMs) to perform a meta-analysis of multiple case-control studies to evaluate the relationship of genetic data to dichotomous traits adjusting for covariates. Unlike the previously developed meta-analysis for sequence kernel association tests (MetaSKATs), which are based on mixed-effect models to make the contributions of major gene loci random, GFLMs are fixed models; i.e., genetic effects of multiple genetic variants are fixed. Based on GFLMs, we developed chi-squared-distributed Rao's efficient score test and likelihood-ratio test (LRT) statistics to test for an association between a complex dichotomous trait and multiple genetic variants. We then performed extensive simulations to evaluate the empirical type I error rates and power performance of the proposed tests. The Rao's efficient score test statistics of GFLMs are very conservative and have higher power than MetaSKATs when some causal variants are rare and some are common. When the causal variants are all rare [i.e., minor allele frequencies (MAF) analysis of eight European studies and detected significant association for 18 genes (P < 3.10 × 10(-6)), tentative association for 2 genes (HHEX and HMGA2; P ≈ 10(-5)), and no association for 2 genes, while MetaSKATs detected none. In addition, the traditional additive-effect model detects association at gene HHEX. GFLMs and related tests can analyze rare or common variants or a combination of the two and can be useful in whole-genome and whole-exome association studies.

  4. A general theory of two-wave mixing in nonlinear media

    DEFF Research Database (Denmark)

    Chi, Mingjun; Huignard, Jean-Pierre; Petersen, Paul Michael

    2009-01-01

    A general theory of two-wave mixing in nonlinear media is presented. Assuming a gain (or absorption) grating and a refractive index grating are generated because of the nonlinear process in a nonlinear medium, the coupled-wave equations of two-wave mixing are derived based on the Maxwell’s wave e...

  5. Implementation of multivariate linear mixed-effects models in the analysis of indoor climate performance experiments

    DEFF Research Database (Denmark)

    Jensen, Kasper Lynge; Spliid, Henrik; Toftum, Jørn

    2011-01-01

    The aim of the current study was to apply multivariate mixed-effects modeling to analyze experimental data on the relation between air quality and the performance of office work. The method estimates in one step the effect of the exposure on a multi-dimensional response variable, and yields impor....... The analysis seems superior to conventional univariate statistics and the information provided may be important for the design of performance experiments in general and for the conclusions that can be based on such studies.......The aim of the current study was to apply multivariate mixed-effects modeling to analyze experimental data on the relation between air quality and the performance of office work. The method estimates in one step the effect of the exposure on a multi-dimensional response variable, and yields...... important information on the correlation between the different dimensions of the response variable, which in this study was composed of both subjective perceptions and a two-dimensional performance task outcome. Such correlation is typically not included in the output from univariate analysis methods. Data...

  6. The Solution Structure and Error Estimation for The Generalized Linear Complementarity Problem

    Directory of Open Access Journals (Sweden)

    Tingfa Yan

    2014-07-01

    Full Text Available In this paper, we consider the generalized linear complementarity problem (GLCP. Firstly, we develop some equivalent reformulations of the problem under milder conditions, and then characterize the solution of the GLCP. Secondly, we also establish the global error estimation for the GLCP by weakening the assumption. These results obtained in this paper can be taken as an extension for the classical linear complementarity problems.

  7. Bounded Real Lemma for Generalized Linear System with Finite Discrete Jumps

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    The strict bounded real lemma for linear system with finite discrete jumps was considered. Especially,the case where D matrices in the system are not assumed to be zero was dealt. Several versions of the bounded real lemma are presented in terms of solution to Riccati differential equations or inequalities with finite discrete jumps.Both the finite and infinite horizon cases are considered. These results generalize the existed bounded real lemma for linear systems.

  8. On necessity proof of strict bounded real lemma for generalized linear systems with finite discrete jumps

    Institute of Scientific and Technical Information of China (English)

    Xiaojun YANG; Zhengxin WENG; Zuohua TIAN

    2004-01-01

    Some preliminary results on strict bounded real lemma for time-varying continuous linear systems are proposed,where uncertainty in initial conditions,terminal cost and extreme of the cost function are dealt with explicitly.Based on these results,a new recursive approach is proposed in the necessity proof of strict bounded real lemma for generalized linear system with finite discrete jumps.

  9. EXISTENCE AND ALGORITHM OF SOLUTIONS FOR GENERAL MULTIVALUED MIXED IMPLICIT QUASI- VARIATIONAL INEQUALITIES

    Institute of Scientific and Technical Information of China (English)

    曾六川

    2003-01-01

    A new class of general multivalued mixed implicit quasi-variational inequalities in a real Hilbert space was introduced, which includes the known class of generalized mixed implicit quasi-variational inequalities as a special case, introduced and studied by Ding Xieping. The auxiliary variational principle technique was applied to solve this class of general multivalued mixed implicit quasi-variational inequalities. Firstly, a new auxiliary variational inequality with a proper convex, lower semicontinuous, binary functional was defined and a suitable functional was chosen so that its unique minimum point is equivalent to the solution of such an auxiliary variational inequality. Secondly, this auxiliary variational inequality was utilized to construct a new iterative algorithm for computing approximate solutions to general multivalued mixed implicit quasi-variational inequalities. Here, the equivalence guarantees that the algorithm can generate a sequence of approximate solutions.Finally, the existence of solutions and convergence of approximate solutions for general multivalued mixed implicit quasi-variational inequalities are proved. Moreover, the new convergerce criteria for the algorithm were provided. Therefore, the results give an affirmative anwer to the open question raised by M . A. Noor , and extend and improve the earlier and recent results for various variational inequalities and complementarity problems including the corresponding results for mixed variational inequalities, mixed quasi-variational inequalities and quasi-complementarity problems involving the single-valued and set-valued mappings in the recent literature.

  10. A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem

    Science.gov (United States)

    Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad

    2010-01-01

    Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.

  11. Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming

    Directory of Open Access Journals (Sweden)

    P. C. Roling

    2008-01-01

    Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.

  12. Internal pilots for a class of linear mixed models with Gaussian and compound symmetric data.

    Science.gov (United States)

    Gurka, Matthew J; Coffey, Christopher S; Muller, Keith E

    2007-09-30

    An internal pilot design uses interim sample size analysis, without interim data analysis, to adjust the final number of observations. The approach helps to choose a sample size sufficiently large (to achieve the statistical power desired), but not too large (which would waste money and time). We report on recent research in cerebral vascular tortuosity (curvature in three dimensions) which would benefit greatly from internal pilots due to uncertainty in the parameters of the covariance matrix used for study planning. Unfortunately, observations correlated across the four regions of the brain and small sample sizes preclude using existing methods. However, as in a wide range of medical imaging studies, tortuosity data have no missing or mistimed data, a factorial within-subject design, the same between-subject design for all responses, and a Gaussian distribution with compound symmetry. For such restricted models, we extend exact, small sample univariate methods for internal pilots to linear mixed models with any between-subject design (not just two groups). Planning a new tortuosity study illustrates how the new methods help to avoid sample sizes that are too small or too large while still controlling the type I error rate.

  13. Application of mixed-integer linear programming in a car seats assembling process

    Directory of Open Access Journals (Sweden)

    Jorge Iván Perez Rave

    2011-12-01

    Full Text Available In this paper, a decision problem involving a car parts manufacturing company is modeled in order to prepare the company for an increase in demand. Mixed-integer linear programming was used with the following decision variables: creating a second shift, purchasing additional equipment, determining the required work force, and other alternatives involving new manners of work distribution that make it possible to separate certain operations from some workplaces and integrate them into others to minimize production costs. The model was solved using GAMS. The solution consisted of programming 19 workers under a configuration that merges two workplaces and separates some operations from some workplaces. The solution did not involve purchasing additional machinery or creating a second shift. As a result, the manufacturing paradigms that had been valid in the company for over 14 years were broken. This study allowed the company to increase its productivity and obtain significant savings. It also shows the benefits of joint work between academia and companies, and provides useful information for professors, students and engineers regarding production and continuous improvement.

  14. Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

    Science.gov (United States)

    Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

    2016-06-02

    Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

  15. Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast

    Science.gov (United States)

    Poos, Alexandra M.; Maicher, André; Dieckmann, Anna K.; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

    2016-01-01

    Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. PMID:26908654

  16. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  17. Mixed Integer Linear Programming For Exact Finite-Horizon Planning In Decentralized Pomdps

    CERN Document Server

    Aras, Raghav; Charpillet, Fran\\ccois

    2007-01-01

    We consider the problem of finding an n-agent joint-policy for the optimal finite-horizon control of a decentralized Pomdp (Dec-Pomdp). This is a problem of very high complexity (NEXP-hard in n >= 2). In this paper, we propose a new mathematical programming approach for the problem. Our approach is based on two ideas: First, we represent each agent's policy in the sequence-form and not in the tree-form, thereby obtaining a very compact representation of the set of joint-policies. Second, using this compact representation, we solve this problem as an instance of combinatorial optimization for which we formulate a mixed integer linear program (MILP). The optimal solution of the MILP directly yields an optimal joint-policy for the Dec-Pomdp. Computational experience shows that formulating and solving the MILP requires significantly less time to solve benchmark Dec-Pomdp problems than existing algorithms. For example, the multi-agent tiger problem for horizon 4 is solved in 72 secs with the MILP whereas existing ...

  18. Mixed and Uniform Double Planar Wire Arrays on University of Michigan's Linear Transformer Driver

    Science.gov (United States)

    Safronova, A. S.; Kantsyrev, V. L.; Shrestha, I. K.; Shlyaptseva, V. V.; Schmidt-Petersen, M. T.; Butcher, C. J.; Petkov, E. E.; Stafford, A.; Cooper, M. C.; Steiner, A. M.; Yager-Elorriaga, D. A.; Jordan, N. M.; Gilgenbach, R. M.

    2016-10-01

    Uniform Double Planar Wire Arrays (DPWA), which consist of two parallel planes of wires of the same material, have previously demonstrated high radiation efficiency, compact size, and usefulness for various applications in experiments on a University-scale high impedance Z-pinch generator. We have already reported on the outcome of the first experiments with uniform Al DPWAs on the University of Michigan's low-impedance Linear Transformer Driver (LTD) MAIZE generator. Here we present the most recent results on the experiments with both uniform (Al wires) and mixed (one plane from Al and another plane from stainless steel or copper wires) DPWAs produced using a diagnostic set similar to the first campaign, including: filtered X-ray diodes, X-ray spectrographs and pinhole cameras, but with a new four frame shadowgraphy system with 2-ns, 532 nm frequency doubled Nd:YAG laser that was further upgraded to a twelve frame shadowgraphy system. Application of different wire planes and much longer period of time observed by the shadowgraphy led to the new results about wire array implosions on the LTD device. Research supported by NNSA under DOE Grant DE-NA0003047.

  19. Automatic design of synthetic gene circuits through mixed integer non-linear programming.

    Science.gov (United States)

    Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias

    2012-01-01

    Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits.

  20. Optimal explicit strong-stability-preserving general linear methods : complete results.

    Energy Technology Data Exchange (ETDEWEB)

    Constantinescu, E. M.; Sandu, A.; Mathematics and Computer Science; Virginia Polytechnic Inst. and State Univ.

    2009-03-03

    This paper constructs strong-stability-preserving general linear time-stepping methods that are well suited for hyperbolic PDEs discretized by the method of lines. These methods generalize both Runge-Kutta (RK) and linear multistep schemes. They have high stage orders and hence are less susceptible than RK methods to order reduction from source terms or nonhomogeneous boundary conditions. A global optimization strategy is used to find the most efficient schemes that have low storage requirements. Numerical results illustrate the theoretical findings.

  1. Longitudinal mathematics development of students with learning disabilities and students without disabilities: a comparison of linear, quadratic, and piecewise linear mixed effects models.

    Science.gov (United States)

    Kohli, Nidhi; Sullivan, Amanda L; Sadeh, Shanna; Zopluoglu, Cengiz

    2015-04-01

    Effective instructional planning and intervening rely heavily on accurate understanding of students' growth, but relatively few researchers have examined mathematics achievement trajectories, particularly for students with special needs. We applied linear, quadratic, and piecewise linear mixed-effects models to identify the best-fitting model for mathematics development over elementary and middle school and to ascertain differences in growth trajectories of children with learning disabilities relative to their typically developing peers. The analytic sample of 2150 students was drawn from the Early Childhood Longitudinal Study - Kindergarten Cohort, a nationally representative sample of United States children who entered kindergarten in 1998. We first modeled students' mathematics growth via multiple mixed-effects models to determine the best fitting model of 9-year growth and then compared the trajectories of students with and without learning disabilities. Results indicate that the piecewise linear mixed-effects model captured best the functional form of students' mathematics trajectories. In addition, there were substantial achievement gaps between students with learning disabilities and students with no disabilities, and their trajectories differed such that students without disabilities progressed at a higher rate than their peers who had learning disabilities. The results underscore the need for further research to understand how to appropriately model students' mathematics trajectories and the need for attention to mathematics achievement gaps in policy. Copyright © 2015 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  2. Stability of Almost Periodic Solution for a General Class of Discontinuous Neural Networks with Mixed Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Yingwei Li

    2013-01-01

    Full Text Available The global exponential stability issues are considered for almost periodic solution of the neural networks with mixed time-varying delays and discontinuous neuron activations. Some sufficient conditions for the existence, uniqueness, and global exponential stability of almost periodic solution are achieved in terms of certain linear matrix inequalities (LMIs, by applying differential inclusions theory, matrix inequality analysis technique, and generalized Lyapunov functional approach. In addition, the existence and asymptotically almost periodic behavior of the solution of the neural networks are also investigated under the framework of the solution in the sense of Filippov. Two simulation examples are given to illustrate the validity of the theoretical results.

  3. Analyticity of solutions of analytic non-linear general elliptic boundary value problems,and some results about linear problems

    Institute of Scientific and Technical Information of China (English)

    WANG Rouhuai

    2006-01-01

    The main aim of this paper is to discuss the problem concerning the analyticity of the solutions of analytic non-linear elliptic boundary value problems.It is proved that if the corresponding first variation is regular in Lopatinski(i) sense,then the solution is analytic up to the boundary.The method of proof really covers the case that the corresponding first variation is regularly elliptic in the sense of Douglis-Nirenberg-Volevich,and hence completely generalize the previous result of C.B.Morrey.The author also discusses linear elliptic boundary value problems for systems of ellip tic partial differential equations where the boundary operators are allowed to have singular integral operators as their coefficients.Combining the standard Fourier transform technique with analytic continuation argument,the author constructs the Poisson and Green's kernel matrices related to the problems discussed and hence obtain some representation formulae to the solutions.Some a priori estimates of Schauder type and Lp type are obtained.

  4. Mixed mono- and multilayers of poly(isocyanide)s with non-linear optically active side chains

    NARCIS (Netherlands)

    Teerenstra, M.N.; Hagting, J.G.; Oostergetel, G.T.; Schouten, A.J.; Devillers, M.A.C.; Nolte, R.J.M.

    1994-01-01

    The properties and structure of Langmuir-Blodgett mono- and multilayers of several poly(isocyanide)s with non-linear optically active side-chains were studied. These polymers formed very rigid layers or layers which appeared to be unstable. To circumvent this problem they were mixed with other poly(

  5. Deliberate practice predicts performance throughout time in adolescent chess players and dropouts: A linear mixed models analysis.

    NARCIS (Netherlands)

    Bruin, de A.B.H.; Smits, N.; Rikers, R.M.J.P.; Schmidt, H.G.

    2008-01-01

    In this study, the longitudinal relation between deliberate practice and performance in chess was examined using a linear mixed models analysis. The practice activities and performance ratings of young elite chess players, who were either in, or had dropped out of the Dutch national chess training,

  6. A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing

    DEFF Research Database (Denmark)

    Fischetti, Martina; Leth, John-Josef; Borchersen, Anders Bech

    2015-01-01

    A Mixed-Integer Linear Programming (MILP) approach is proposed to optimize the turbine allocation and inter-array offshore cable routing. The two problems are considered with a two steps strategy, solving the layout problem first and then the cable problem. We give an introduction to both problem...

  7. Deliberate practice predicts performance throughout time in adolescent chess players and dropouts: A linear mixed models analysis.

    NARCIS (Netherlands)

    Bruin, de A.B.H.; Smits, N.; Rikers, R.M.J.P.; Schmidt, H.G.

    2008-01-01

    In this study, the longitudinal relation between deliberate practice and performance in chess was examined using a linear mixed models analysis. The practice activities and performance ratings of young elite chess players, who were either in, or had dropped out of the Dutch national chess training,

  8. Linear and nonlinear associations between general intelligence and personality in Project TALENT.

    Science.gov (United States)

    Major, Jason T; Johnson, Wendy; Deary, Ian J

    2014-04-01

    Research on the relations of personality traits to intelligence has primarily been concerned with linear associations. Yet, there are no a priori reasons why linear relations should be expected over nonlinear ones, which represent a much larger set of all possible associations. Using 2 techniques, quadratic and generalized additive models, we tested for linear and nonlinear associations of general intelligence (g) with 10 personality scales from Project TALENT (PT), a nationally representative sample of approximately 400,000 American high school students from 1960, divided into 4 grade samples (Flanagan et al., 1962). We departed from previous studies, including one with PT (Reeve, Meyer, & Bonaccio, 2006), by modeling latent quadratic effects directly, controlling the influence of the common factor in the personality scales, and assuming a direction of effect from g to personality. On the basis of the literature, we made 17 directional hypotheses for the linear and quadratic associations. Of these, 53% were supported in all 4 male grades and 58% in all 4 female grades. Quadratic associations explained substantive variance above and beyond linear effects (mean R² between 1.8% and 3.6%) for Sociability, Maturity, Vigor, and Leadership in males and Sociability, Maturity, and Tidiness in females; linear associations were predominant for other traits. We discuss how suited current theories of the personality-intelligence interface are to explain these associations, and how research on intellectually gifted samples may provide a unique way of understanding them. We conclude that nonlinear models can provide incremental detail regarding personality and intelligence associations.

  9. Mixed models for predictive modeling in actuarial science

    NARCIS (Netherlands)

    Antonio, K.; Zhang, Y.

    2012-01-01

    We start with a general discussion of mixed (also called multilevel) models and continue with illustrating specific (actuarial) applications of this type of models. Technical details on (linear, generalized, non-linear) mixed models follow: model assumptions, specifications, estimation techniques

  10. Interior-point algorithm based on general kernel function for monotone linear complementarity problem

    Institute of Scientific and Technical Information of China (English)

    LIU Yong; BAI Yan-qin

    2009-01-01

    A polynomial interior-point algorithm is presented for monotone linear complementarity problem (MLCP) based on:a class of kernel functions with the general barrier term, which are called general kernel functions. Under the mild conditions for the barrier term, the complexity bound of algorithm in terms of such kernel function and its derivatives is obtained. The approach is actually an extension of the existing work which only used the specific kernel functions for the MLCP.

  11. General linear methods and friends: Toward efficient solutions of multiphysics problems

    Science.gov (United States)

    Sandu, Adrian

    2017-07-01

    Time dependent multiphysics partial differential equations are of great practical importance as they model diverse phenomena that appear in mechanical and chemical engineering, aeronautics, astrophysics, meteorology and oceanography, financial modeling, environmental sciences, etc. There is no single best time discretization for the complex multiphysics systems of practical interest. We discuss "multimethod" approaches that combine different time steps and discretizations using the rigourous frameworks provided by Partitioned General Linear Methods and Generalize-structure Additive Runge Kutta Methods..

  12. Factors Affecting Malnutrition in Developing Countries: A Linear Mixed Model Approach

    Directory of Open Access Journals (Sweden)

    Sohair F. Higazi

    2012-11-01

    Full Text Available  AbstractThe main objective of this study is to pinpoint the main factors that affect the percentage who suffers of malnutrition in developing countries. Three locations are randomly chosen: Asia, Africa, and Middle east and North Africa ( MENA; A total of 96 countries were chosen randomly from 137  developing countries of the three locations; and were cross classified by " Location" and  " Human Development Index (HDI as high, middle, and low (UNDP,  2005.  Data for the study was compiled from FAO (2005. The analysis started with seven explanatory variables and the dependent variable; however, stepwise regression reveals that the average Protein intake and Infant mortality rate were the only two significant variables. "Location and "HDI" are dummy coded and OLS regression is performed using the two significant variables, but the only significant variable was the "average protein intake". OLS multiple regression Model is re-applied to the data using dummy variables technique with interaction with the "average Protein intake", nine regression equations were reached.The Linear Mixed effect Models are also applied, using "location" as the random factor and "HDI" as the fixed factor. Five models were applied: (1 a null model (baseline modelwhere no predictors are introduced to the model; (2 the fixed model: where predictors used are the  covariate and the HDI; (3 the random model: where predictors used are  the covariate and Location ; (4 the mixed model: where predictors used are the covariate and the HDI I  ( fixed and the location( random; and (5 the random coefficient model: where predictors used are  the covariate ,  the HDI Index  and the location but produces different prediction equations that differ in slopes and intercepts. Models are compared based on information criterions. The random coefficient model produces the least criterion values and thus fits better than all previous ones. A comparison between the Random Coefficient

  13. Factors Affecting Malnutrition in Developing Countries: A Linear Mixed Model Approach

    Directory of Open Access Journals (Sweden)

    Sohair F. Higazi

    2012-11-01

    Full Text Available  AbstractThe main objective of this study is to pinpoint the main factors that affect the percentage who suffers of malnutrition in developing countries. Three locations are randomly chosen: Asia, Africa, and Middle east and North Africa ( MENA; A total of 96 countries were chosen randomly from 137  developing countries of the three locations; and were cross classified by " Location" and  " Human Development Index (HDI as high, middle, and low (UNDP,  2005.  Data for the study was compiled from FAO (2005. The analysis started with seven explanatory variables and the dependent variable; however, stepwise regression reveals that the average Protein intake and Infant mortality rate were the only two significant variables. "Location and "HDI" are dummy coded and OLS regression is performed using the two significant variables, but the only significant variable was the "average protein intake". OLS multiple regression Model is re-applied to the data using dummy variables technique with interaction with the "average Protein intake", nine regression equations were reached.The Linear Mixed effect Models are also applied, using "location" as the random factor and "HDI" as the fixed factor. Five models were applied: (1 a null model (baseline modelwhere no predictors are introduced to the model; (2 the fixed model: where predictors used are the  covariate and the HDI; (3 the random model: where predictors used are  the covariate and Location ; (4 the mixed model: where predictors used are the covariate and the HDI I  ( fixed and the location( random; and (5 the random coefficient model: where predictors used are  the covariate ,  the HDI Index  and the location but produces different prediction equations that differ in slopes and intercepts. Models are compared based on information criterions. The random coefficient model produces the least criterion values and thus fits better than all previous ones. A comparison between the Random Coefficient

  14. Looking-Free Mixed hp Finite Element Methods for Linear and Geometrically Nonlinear Elasticity

    Science.gov (United States)

    1997-06-09

    hp mixed methods has been addressed by Stenberg and Suri[20]. They identify sufficient conditions for selecting mixed method spaces on parallelogram...spaces of piecewise polynomials. Math. Modeling Num. Anal., 19:111-143, 1985. [20] R. Stenberg and M. Suri. Mixed hp finite element methods for

  15. Implementation of a simple model for linear and nonlinear mixing at unstable fluid interfaces in hydrodynamics codes

    Energy Technology Data Exchange (ETDEWEB)

    Ramshaw, J D

    2000-10-01

    A simple model was recently described for predicting the time evolution of the width of the mixing layer at an unstable fluid interface [J. D. Ramshaw, Phys. Rev. E 58, 5834 (1998); ibid. 61, 5339 (2000)]. The ordinary differential equations of this model have been heuristically generalized into partial differential equations suitable for implementation in multicomponent hydrodynamics codes. The central ingredient in this generalization is a nun-diffusional expression for the species mass fluxes. These fluxes describe the relative motion of the species, and thereby determine the local mixing rate and spatial distribution of mixed fluid as a function of time. The generalized model has been implemented in a two-dimensional hydrodynamics code. The model equations and implementation procedure are summarized, and comparisons with experimental mixing data are presented.

  16. A general non-linear optimization algorithm for lower bound limit analysis

    DEFF Research Database (Denmark)

    Krabbenhøft, Kristian; Damkilde, Lars

    2003-01-01

    The non-linear programming problem associated with the discrete lower bound limit analysis problem is treated by means of an algorithm where the need to linearize the yield criteria is avoided. The algorithm is an interior point method and is completely general in the sense that no particular...... finite element discretization or yield criterion is required. As with interior point methods for linear programming the number of iterations is affected only little by the problem size. Some practical implementation issues are discussed with reference to the special structure of the common lower bound...... load optimization problem. and finally the efficiency and accuracy of the method is demonstrated by means of examples of plate and slab structures obeying different non-linear yield criteria. Copyright (C) 2002 John Wiley Sons. Ltd....

  17. SELECTION OF THE LINEAR COMBINING VECTOR G OF THE GENERALIZED SELF-SHRINKING GENERATORS

    Institute of Scientific and Technical Information of China (English)

    Dong Lihua; Zeng Yong; Hu Yupu

    2006-01-01

    Given an m-sequence, the main factor influencing the least period of the Generalized Self-Shrinking (GSS) sequence is the selection of the linear combining vector G. Based on the calculation of the minimalpolynomial ofL GSS sequences and the comparison of their degrees, an algorithm for selecting the linear combining vector G is presented, which is simple to understand, to implement and to prove. By using this method,much more than 2L-1 linear combining vectors G of the desired properties will be resulted. Thus in the practical application the linear combining vector G can be chosen with great arbitrariness. Additionally, this algorithm can be extended to any finite field easily.

  18. On the distribution of discounted loss reserves using generalized linear models

    NARCIS (Netherlands)

    Hoedemakers, T.; Beirlant, J.; Goovaerts, M.J.; Dhaene, J.

    2005-01-01

    Renshaw and Verrall [11] specified the generalized linear model (GLM) underlying the chain-ladder technique and suggested some other GLMs which might be useful in claims reserving. The purpose of this paper is to construct bounds for the discounted loss reserve within the framework of GLMs. Exact

  19. Large-Sample Theory for Generalized Linear Models with Non-natural Link and Random Variates

    Institute of Scientific and Technical Information of China (English)

    Jie-li Ding; Xi-ru Chen

    2006-01-01

    For generalized linear models (GLM), in the case that the regressors are stochastic and have different distributions and the observations of the responses may have different dimensionality, the asymptotic theory of the maximum likelihood estimate (MLE) of the parameters are studied under the assumption of a non-natural link function.

  20. Regression Is a Univariate General Linear Model Subsuming Other Parametric Methods as Special Cases.

    Science.gov (United States)

    Vidal, Sherry

    Although the concept of the general linear model (GLM) has existed since the 1960s, other univariate analyses such as the t-test and the analysis of variance models have remained popular. The GLM produces an equation that minimizes the mean differences of independent variables as they are related to a dependent variable. From a computer printout…

  1. Asymptotic Properties of the Maximum Likelihood Estimate in Generalized Linear Models with Stochastic Regressors

    Institute of Scientific and Technical Information of China (English)

    Jie Li DING; Xi Ru CHEN

    2006-01-01

    For generalized linear models (GLM), in case the regressors are stochastic and have different distributions, the asymptotic properties of the maximum likelihood estimate (MLE)(β^)n of the parameters are studied. Under reasonable conditions, we prove the weak, strong consistency and asymptotic normality of(β^)n.

  2. The microcomputer scientific software series 2: general linear model--regression.

    Science.gov (United States)

    Harold M. Rauscher

    1983-01-01

    The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

  3. Generalized Partially Linear Regression with Misclassified Data and an Application to Labour Market Transitions

    DEFF Research Database (Denmark)

    Dlugosz, Stephan; Mammen, Enno; Wilke, Ralf

    2017-01-01

    observations from Germany. It is shown that estimated marginal effects of a number of covariates are sizeably affected by misclassification and missing values in the analysis data. The proposed generalized partially linear regression extends existing models by allowing a misclassified discrete covariate...

  4. More on Generalizations and Modifications of Iterative Methods for Solving Large Sparse Indefinite Linear Systems

    Directory of Open Access Journals (Sweden)

    Jen-Yuan Chen

    2014-01-01

    Full Text Available Continuing from the works of Li et al. (2014, Li (2007, and Kincaid et al. (2000, we present more generalizations and modifications of iterative methods for solving large sparse symmetric and nonsymmetric indefinite systems of linear equations. We discuss a variety of iterative methods such as GMRES, MGMRES, MINRES, LQ-MINRES, QR MINRES, MMINRES, MGRES, and others.

  5. Generalized Jacobi and Gauss-Seidel Methods for Solving Linear System of Equations

    Institute of Scientific and Technical Information of China (English)

    Davod Khojasteh Salkuyeh

    2007-01-01

    The Jacobi and Gauss-Seidel algorithms are among the stationary iterative methods for solving linear system of equations. They are now mostly used as preconditioners for the popular iterative solvers. In this paper a generalization of these methods are proposed and their convergence properties are studied. Some numerical experiments are given to show the efficiency of the new methods.

  6. ESTIMATION METHOD FOR SOLUTIONS TO GENERAL LINEAR SYSTEM OF VOLTERRAINTEGRAL INEQUALITIES INVOLVING ITERATED INTEGRAL FUNCTIONALS

    Institute of Scientific and Technical Information of China (English)

    MA Qinghua; YANG Enhao

    2000-01-01

    An estimation method for solutions to the general linear system of Volterratype integral inequalities containing several iterated integral functionals is obtained. This method is based on a result proved by the present second author in Journ. Math. Anal. Appl.(1984). A certain two-dimensional system of nonlinear ordinary differential equations is also discussed to demonstrate the usefulness of our method.

  7. Rate of strong consistency of quasi maximum likelihood estimate in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    2004-01-01

    [1]McCullagh, P., Nelder, J. A., Generalized Linear Models, New York: Chapman and Hall, 1989.[2]Wedderbum, R. W. M., Quasi-likelihood functions, generalized linear models and Gauss-Newton method,Biometrika, 1974, 61:439-447.[3]Fahrmeir, L., Maximum likelihood estimation in misspecified generalized linear models, Statistics, 1990, 21:487-502.[4]Fahrmeir, L., Kaufmann, H., Consistency and asymptotic normality of the maximum likelihood estimator in generalized linear models, Ann. Statist., 1985, 13: 342-368.[5]Melder, J. A., Pregibon, D., An extended quasi-likelihood function, Biometrika, 1987, 74: 221-232.[6]Bennet, G., Probability inequalities for the sum of independent random variables, JASA, 1962, 57: 33-45.[7]Stout, W. F., Almost Sure Convergence, New York:Academic Press, 1974.[8]Petrov, V, V., Sums of Independent Random Variables, Berlin, New York: Springer-Verlag, 1975.

  8. General treatment of the non-linear Rsub(Xi) gauge condition

    Energy Technology Data Exchange (ETDEWEB)

    Girardi, G.; Malleville, C.; Sorba, P. (Grenoble-1 Univ., 74 - Annecy (France). Lab. de Physique des Particules)

    1982-11-04

    It is shown that the non-linear Rsub(xi) gauge condition already introduced for the standard SU(2)xU(1) model can be generalized for any gauge model with the same type of simplification, namely the suppression of any coupling of the form: (massless gauge boson)x(massive gauge boson)x(unphysical Higgs).

  9. ON THE SOLVABILITY OF GENERAL LINEAR METHODS FOR DISSIPATIVE DYNAMICAL SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    Ai-guo Xiao

    2000-01-01

    The main purpose of the present paper is to examine the existence and local uniqueness of solutions of the implicit equations arising in the application of a weakly algebraically stable general linear methods to dissipative dynamical systems, and to extend the existing relevant results of Runge-Kutta methods by Humphries and Stuart(1994).

  10. A differential-geometric approach to generalized linear models with grouped predictors

    NARCIS (Netherlands)

    Augugliaro, Luigi; Mineo, Angelo M.; Wit, Ernst C.

    2016-01-01

    We propose an extension of the differential-geometric least angle regression method to perform sparse group inference in a generalized linear model. An efficient algorithm is proposed to compute the solution curve. The proposed group differential-geometric least angle regression method has important

  11. Selecting a linear mixed model for longitudinal data: repeated measures analysis of variance, covariance pattern model, and growth curve approaches.

    Science.gov (United States)

    Liu, Siwei; Rovine, Michael J; Molenaar, Peter C M

    2012-03-01

    With increasing popularity, growth curve modeling is more and more often considered as the 1st choice for analyzing longitudinal data. Although the growth curve approach is often a good choice, other modeling strategies may more directly answer questions of interest. It is common to see researchers fit growth curve models without considering alterative modeling strategies. In this article we compare 3 approaches for analyzing longitudinal data: repeated measures analysis of variance, covariance pattern models, and growth curve models. As all are members of the general linear mixed model family, they represent somewhat different assumptions about the way individuals change. These assumptions result in different patterns of covariation among the residuals around the fixed effects. In this article, we first indicate the kinds of data that are appropriately modeled by each and use real data examples to demonstrate possible problems associated with the blanket selection of the growth curve model. We then present a simulation that indicates the utility of Akaike information criterion and Bayesian information criterion in the selection of a proper residual covariance structure. The results cast doubt on the popular practice of automatically using growth curve modeling for longitudinal data without comparing the fit of different models. Finally, we provide some practical advice for assessing mean changes in the presence of correlated data.

  12. Parameterization of general Z-y-Z’ mixing in an electroweak chiral theory

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ying; WANG Qing

    2012-01-01

    A new general parameterization with eight mixing parameters among Z,γ and an extra neutral gauge boson Z' is proposed and subjected to phenomenological analysis. We show that in addition to the conventional Weinberg angle θw,there are seven other phenomenological parameters,G',ξ,η,θl,θr,r and l,for the most general Z-y-Z' mixings,in which parameter G' arises due to the presence of an extra Stueckelbergtype mass coupling.Combined with the conventional Z-Z' mass mixing angle θ',the remaining six parameters,ξ,η,θl- θ',θr-θ',r and l,are caused by general kinetic mixing.In all eight phenomenological parameters,θw,G',ξ,η,θl,θr,r and l,we can determine the Z-Z' mass mixing angle θ' and the mass ratio Mz/Mz,.The Z-γ-Z' mixing that we discuss are based on the model-independent description of the extended electroweak chiral Lagrangian (EWCL) previously proposed by us:In addition,we show that there are eight corresponding independent theoretical coefficients in our EWCL,which are fully fixed by our eight phenomenological mixing parameters.We further find that the experimental measurability of these eight parameters does not rely on the extended neutral current for Z',but depends on the Z-Z' mass ratio.

  13. Advancing the science of spatial neglect rehabilitation: an improved statistical approach with mixed linear modeling

    Directory of Open Access Journals (Sweden)

    Kelly M Goedert

    2013-05-01

    Full Text Available Valid research on neglect rehabilitation demands a statistical approach commensurate with the characteristics of neglect rehabilitation data: Neglect arises from impairment in distinct brain networks leading to large between-subject variability in baseline symptoms and recovery trajectories. Studies enrolling medically-ill, disabled patients, may suffer from missing, unbalanced data, and small sample sizes. Finally, assessment of rehabilitation requires a description of continuous recovery trajectories. Unfortunately, the statistical method currently employed in most studies of neglect treatment (repeated-measures ANOVA does not well-address these issues. Here we review an alternative, mixed linear modeling (MLM, that is more appropriate for assessing change over time. MLM better accounts for between-subject heterogeneity in baseline neglect severity and in recovery trajectory. MLM does not require complete or balanced data, nor does it make strict assumptions regarding the data structure. Furthermore, because MLM better models between-subject heterogeneity it often results in increased power to observe treatment effects with smaller samples. After reviewing current practices in the field, and the assumptions of repeated-measures ANOVA, we provide an introduction to MLM. We review its assumptions, uses, advantages and disadvantages. Using real and simulated data, we illustrate how MLM may improve the ability to detect effects of treatment over ANOVA, particularly with the small samples typical of neglect research. Furthermore, our simulation analyses result in recommendations for the design of future rehabilitation studies. Because between-subject heterogeneity is one important reason why studies of neglect treatments often yield conflicting results, employing statistical procedures that model this heterogeneity more accurately will increase the efficiency of our efforts to find treatments to improve the lives of individuals with neglect.

  14. Behavior of solution set for bilevel generalized mixed equilibrium problems in topological vector spaces

    Institute of Scientific and Technical Information of China (English)

    丁协平

    2014-01-01

    A new bilevel generalized mixed equilibrium problem (BGMEP) is introduced and studied in topological vector spaces. By using a minimax inequality, the existence of solutions and the behavior of solution set for the BGMEP are studied under quite mild conditions. These results are new and generalize some recent results in this field.

  15. Personnel planning in general practices: development and testing of a skill mix analysis method.

    NARCIS (Netherlands)

    Eitzen-Strassel, J. von; Vrijhoef, H.J.M.; Derckx, E.W.C.C.; Bakker, D.H. de

    2014-01-01

    Background: General practitioners (GPs) have to match patients’ demands with the mix of their practice staff’s competencies. However, apart from some general principles, there is little guidance on recruiting new staff. The purpose of this study was to develop and test a method which would allow GPs

  16. Personnel planning in general practices : Development and testing of a skill mix analysis method

    NARCIS (Netherlands)

    von Eitzen-Strassel, J.; Vrijhoef, H.J.M.; Derckx, E.W.C.C.; de Bakker, D.H.

    2014-01-01

    Background General practitioners (GPs) have to match patients’ demands with the mix of their practice staff’s competencies. However, apart from some general principles, there is little guidance on recruiting new staff. The purpose of this study was to develop and test a method which would allow GPs

  17. PREDICTOR-CORRECTOR ALGORITHMS FOR SOLVING GENERALIZED MIXED IMPLICIT QUASI-EQUILIBRIUM PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    DING Xie-ping; LIN Yen-cherng; YAO Jen-chih

    2006-01-01

    A new class of generalized mixed implicit quasi-equilibrium problems (GMIQEP) with four-functions is introduced and studied. The new class of equilibrium problems includes many known generalized equilibrium problems and generalized mixed implicit quasi-variational inequality problems as many special cases. By employing the auxiliary principle technique, some predictor-corrector iterative algorithms for solving the GMIQEP are suggested and analyzed. The convergence of the suggested algorithm only requires the continuity and the partially relaxed implicit strong monotonicity of the mappings.

  18. A NEW SELF-ADAPTIVE ITERATIVE METHOD FOR GENERAL MIXED QUASI VARIATIONAL INEQUALITIES

    Institute of Scientific and Technical Information of China (English)

    Abdellah Bnouhachem; Mohamed Khalfaoui; Hafida Benazza

    2008-01-01

    The general mixed quasi variational inequality containing a nonlinear term ψ is a useful and an important generalization of variational inequalities. The projection method can not be applied to solve this problem due to the presence of nonlinear term. It is well known that the variational inequalities involving the nonlinear term ψ are equivalent to the fixed point problems and re, solvent equations. In this article, the authors use these alternative equivalent formulations to suggest and analyze a new self-adaptive iterative method for solving general mixed quasi variational inequalities. Global convergence of the new method is proved. An example is given to illustrate the efficiency of the proposed method.

  19. Strong consistency of maximum quasi-likelihood estimates in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    YiN; Changming; ZHAO; Lincheng

    2005-01-01

    In a generalized linear model with q × 1 responses, bounded and fixed p × qregressors Zi and general link function, under the most general assumption on the mini-mum eigenvalue of∑ni=1n ZiZ'i, the moment condition on responses as weak as possibleand other mild regular conditions, we prove that with probability one, the quasi-likelihoodequation has a solutionβn for all large sample size n, which converges to the true regres-sion parameterβo. This result is an essential improvement over the relevant results in literature.

  20. Generalized model of double random phase encoding based on linear algebra

    Science.gov (United States)

    Nakano, Kazuya; Takeda, Masafumi; Suzuki, Hiroyuki; Yamaguchi, Masahiro

    2013-01-01

    We propose a generalized model for double random phase encoding (DRPE) based on linear algebra. We defined the DRPE procedure in six steps. The first three steps form an encryption procedure, while the later three steps make up a decryption procedure. We noted that the first (mapping) and second (transform) steps can be generalized. As an example of this generalization, we used 3D mapping and a transform matrix, which is a combination of a discrete cosine transform and two permutation matrices. Finally, we investigated the sensitivity of the proposed model to errors in the decryption key.

  1. Generalized linear models with random effects unified analysis via H-likelihood

    CERN Document Server

    Lee, Youngjo; Pawitan, Yudi

    2006-01-01

    Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...

  2. A Hierarchical Generalized Linear Model in Combination with Dispersion Modeling to Improve Sib-Pair Linkage Analysis.

    Science.gov (United States)

    Lee, Woojoo; Kim, Jeonghwan; Lee, Youngjo; Park, Taesung; Suh, Young Ju

    2015-01-01

    We explored a hierarchical generalized linear model (HGLM) in combination with dispersion modeling to improve the sib-pair linkage analysis based on the revised Haseman-Elston regression model for a quantitative trait. A dispersion modeling technique was investigated for sib-pair linkage analysis using simulation studies and real data applications. We considered 4 heterogeneous dispersion settings according to a signal-to-noise ratio (SNR) in the various statistical models based on the Haseman-Elston regression model. Our numerical studies demonstrated that susceptibility loci could be detected well by modeling the dispersion parameter appropriately. In particular, the HGLM had better performance than the linear regression model and the ordinary linear mixed model when the SNR is low, i.e., when substantial noise was present in the data. The study shows that the HGLM in combination with dispersion modeling can be utilized to identify multiple markers showing linkage to familial complex traits accurately. Appropriate dispersion modeling might be more powerful to identify markers closest to the major genes which determine a quantitative trait. © 2015 S. Karger AG, Basel.

  3. Modelling lactation curve for milk fat to protein ratio in Iranian buffaloes (Bubalus bubalis) using non-linear mixed models.

    Science.gov (United States)

    Hossein-Zadeh, Navid Ghavi

    2016-08-01

    The aim of this study was to compare seven non-linear mathematical models (Brody, Wood, Dhanoa, Sikka, Nelder, Rook and Dijkstra) to examine their efficiency in describing the lactation curves for milk fat to protein ratio (FPR) in Iranian buffaloes. Data were 43 818 test-day records for FPR from the first three lactations of Iranian buffaloes which were collected on 523 dairy herds in the period from 1996 to 2012 by the Animal Breeding Center of Iran. Each model was fitted to monthly FPR records of buffaloes using the non-linear mixed model procedure (PROC NLMIXED) in SAS and the parameters were estimated. The models were tested for goodness of fit using Akaike's information criterion (AIC), Bayesian information criterion (BIC) and log maximum likelihood (-2 Log L). The Nelder and Sikka mixed models provided the best fit of lactation curve for FPR in the first and second lactations of Iranian buffaloes, respectively. However, Wood, Dhanoa and Sikka mixed models provided the best fit of lactation curve for FPR in the third parity buffaloes. Evaluation of first, second and third lactation features showed that all models, except for Dijkstra model in the third lactation, under-predicted test time at which daily FPR was minimum. On the other hand, minimum FPR was over-predicted by all equations. Evaluation of the different models used in this study indicated that non-linear mixed models were sufficient for fitting test-day FPR records of Iranian buffaloes.

  4. Consensus of Continuous-Time Multiagent Systems with General Linear Dynamics and Nonuniform Sampling

    Directory of Open Access Journals (Sweden)

    Yanping Gao

    2013-01-01

    Full Text Available This paper studies the consensus problem of multiple agents with general linear continuous-time dynamics. It is assumed that the information transmission among agents is intermittent; namely, each agent can only obtain the information of other agents at some discrete times, where the discrete time intervals may not be equal. Some sufficient conditions for consensus in the cases of state feedback and static output feedback are established, and it is shown that if the controller gain and the upper bound of discrete time intervals satisfy certain linear matrix inequality, then consensus can be reached. Simulations are performed to validate the theoretical results.

  5. H∞ filtering of Markov jump linear systems with general transition probabilities and output quantization.

    Science.gov (United States)

    Shen, Mouquan; Park, Ju H

    2016-07-01

    This paper addresses the H∞ filtering of continuous Markov jump linear systems with general transition probabilities and output quantization. S-procedure is employed to handle the adverse influence of the quantization and a new approach is developed to conquer the nonlinearity induced by uncertain and unknown transition probabilities. Then, sufficient conditions are presented to ensure the filtering error system to be stochastically stable with the prescribed performance requirement. Without specified structure imposed on introduced slack variables, a flexible filter design method is established in terms of linear matrix inequalities. The effectiveness of the proposed method is validated by a numerical example.

  6. Hierarchical Shrinkage Priors and Model Fitting for High-dimensional Generalized Linear Models

    Science.gov (United States)

    Yi, Nengjun; Ma, Shuangge

    2013-01-01

    Genetic and other scientific studies routinely generate very many predictor variables, which can be naturally grouped, with predictors in the same groups being highly correlated. It is desirable to incorporate the hierarchical structure of the predictor variables into generalized linear models for simultaneous variable selection and coefficient estimation. We propose two prior distributions: hierarchical Cauchy and double-exponential distributions, on coefficients in generalized linear models. The hierarchical priors include both variable-specific and group-specific tuning parameters, thereby not only adopting different shrinkage for different coefficients and different groups but also providing a way to pool the information within groups. We fit generalized linear models with the proposed hierarchical priors by incorporating flexible expectation-maximization (EM) algorithms into the standard iteratively weighted least squares as implemented in the general statistical package R. The methods are illustrated with data from an experiment to identify genetic polymorphisms for survival of mice following infection with Listeria monocytogenes. The performance of the proposed procedures is further assessed via simulation studies. The methods are implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). PMID:23192052

  7. On the reformulation of topology optimization problems as linear or convex quadratic mixed 0–1 programs

    DEFF Research Database (Denmark)

    Stolpe, Mathias

    2007-01-01

    We consider equivalent reformulations of nonlinear mixed 0–1 optimization problems arising from a broad range of recent applications of topology optimization for the design of continuum structures and composite materials. We show that the considered problems can equivalently be cast as either...... linear or convex quadratic mixed 0–1 programs. The reformulations provide new insight into the structure of the problems and may provide a foundation for the development of new methods and heuristics for solving topology optimization problems. The applications considered are maximum stiffness design...

  8. On the reformulation of topology optimization problems as linear or convex quadratic mixed 0-1 programs

    DEFF Research Database (Denmark)

    Stolpe, Mathias

    2004-01-01

    We consider equivalent reformulations of nonlinear mixed 0-1 optimization problems arising from a broad range of recent applications of topology optimization for the design of continuum structures and composite materials. It is shown that the considered problems may equivalently be cast as either...... linear or as convex quadratic mixed 0-1 programs. The reformulations provide new insight into the structure of the problems and may provide a foundation for the development of new methods and heuristics for solving topology optimization problems. The applications considered are maximum stiffness design...

  9. A TRUST REGION ALGORITHM VIA BILEVEL LINEAR PROGRAMMING FOR SOLVING THE GENERAL MULTICOMMODITY MINIMAL COST FLOW PROBLEMS

    Institute of Scientific and Technical Information of China (English)

    ZhuDetong

    2004-01-01

    This paper proposes a nonmonotonic backtracking trust region algorithm via bilevel linear programming for solving the general multicommodity minimal cost flow problems. Using the duality theory of the linear programming and convex theory, the generalized directional derivative of the general multicommodity minimal cost flow problems is derived. The global convergence and superlinear convergence rate of the proposed algorithm are established under some mild conditions.

  10. An Optimally Generalized Steepest-Descent Algorithm for Solving Ill-Posed Linear Systems

    Directory of Open Access Journals (Sweden)

    Chein-Shan Liu

    2013-01-01

    Full Text Available It is known that the steepest-descent method converges normally at the first few iterations, and then it slows down. We modify the original steplength and descent direction by an optimization argument with the new steplength as being a merit function to be maximized. An optimal iterative algorithm with m-vector descent direction in a Krylov subspace is constructed, of which the m optimal weighting parameters are solved in closed-form to accelerate the convergence speed in solving ill-posed linear problems. The optimally generalized steepest-descent algorithm (OGSDA is proven to be convergent with very fast convergence speed, accurate and robust against noisy disturbance, which is confirmed by numerical tests of some well-known ill-posed linear problems and linear inverse problems.

  11. Implementation of dual-energy technique for virtual monochromatic and linearly mixed CBCTs

    Energy Technology Data Exchange (ETDEWEB)

    Li Hao; Giles, William; Ren Lei; Bowsher, James; Yin Fangfang [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27710 (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2012-10-15

    Purpose: To implement dual-energy imaging technique for virtual monochromatic (VM) and linearly mixed (LM) cone beam CTs (CBCTs) and to demonstrate their potential applications in metal artifact reduction and contrast enhancement in image-guided radiation therapy (IGRT). Methods: A bench-top CBCT system was used to acquire 80 kVp and 150 kVp projections, with an additional 0.8 mm tin filtration. To implement the VM technique, these projections were first decomposed into acrylic and aluminum basis material projections to synthesize VM projections, which were then used to reconstruct VM CBCTs. The effect of VM CBCT on the metal artifact reduction was evaluated with an in-house titanium-BB phantom. The optimal VM energy to maximize contrast-to-noise ratio (CNR) for iodine contrast and minimize beam hardening in VM CBCT was determined using a water phantom containing two iodine concentrations. The LM technique was implemented by linearly combining the low-energy (80 kVp) and high-energy (150 kVp) CBCTs. The dose partitioning between low-energy and high-energy CBCTs was varied (20%, 40%, 60%, and 80% for low-energy) while keeping total dose approximately equal to single-energy CBCTs, measured using an ion chamber. Noise levels and CNRs for four tissue types were investigated for dual-energy LM CBCTs in comparison with single-energy CBCTs at 80, 100, 125, and 150 kVp. Results: The VM technique showed substantial reduction of metal artifacts at 100 keV with a 40% reduction in the background standard deviation compared to a 125 kVp single-energy scan of equal dose. The VM energy to maximize CNR for both iodine concentrations and minimize beam hardening in the metal-free object was 50 keV and 60 keV, respectively. The difference of average noise levels measured in the phantom background was 1.2% between dual-energy LM CBCTs and equivalent-dose single-energy CBCTs. CNR values in the LM CBCTs of any dose partitioning are better than those of 150 kVp single-energy CBCTs. The

  12. General job stress: a unidimensional measure and its non-linear relations with outcome variables.

    Science.gov (United States)

    Yankelevich, Maya; Broadfoot, Alison; Gillespie, Jennifer Z; Gillespie, Michael A; Guidroz, Ashley

    2012-04-01

    This article aims to examine the non-linear relations between a general measure of job stress [Stress in General (SIG)] and two outcome variables: intentions to quit and job satisfaction. In so doing, we also re-examine the factor structure of the SIG and determine that, as a two-factor scale, it obscures non-linear relations with outcomes. Thus, in this research, we not only test for non-linear relations between stress and outcome variables but also present an updated version of the SIG scale. Using two distinct samples of working adults (sample 1, N = 589; sample 2, N = 4322), results indicate that a more parsimonious eight-item SIG has better model-data fit than the 15-item two-factor SIG and that the eight-item SIG has non-linear relations with job satisfaction and intentions to quit. Specifically, the revised SIG has an inverted curvilinear J-shaped relation with job satisfaction such that job satisfaction drops precipitously after a certain level of stress; the SIG has a J-shaped curvilinear relation with intentions to quit such that turnover intentions increase exponentially after a certain level of stress.

  13. Semiparametric Analysis of Heterogeneous Data Using Varying-Scale Generalized Linear Models.

    Science.gov (United States)

    Xie, Minge; Simpson, Douglas G; Carroll, Raymond J

    2008-01-01

    This article describes a class of heteroscedastic generalized linear regression models in which a subset of the regression parameters are rescaled nonparametrically, and develops efficient semiparametric inferences for the parametric components of the models. Such models provide a means to adapt for heterogeneity in the data due to varying exposures, varying levels of aggregation, and so on. The class of models considered includes generalized partially linear models and nonparametrically scaled link function models as special cases. We present an algorithm to estimate the scale function nonparametrically, and obtain asymptotic distribution theory for regression parameter estimates. In particular, we establish that the asymptotic covariance of the semiparametric estimator for the parametric part of the model achieves the semiparametric lower bound. We also describe bootstrap-based goodness-of-scale test. We illustrate the methodology with simulations, published data, and data from collaborative research on ultrasound safety.

  14. A cautionary note on generalized linear models for covariance of unbalanced longitudinal data

    KAUST Repository

    Huang, Jianhua Z.

    2012-03-01

    Missing data in longitudinal studies can create enormous challenges in data analysis when coupled with the positive-definiteness constraint on a covariance matrix. For complete balanced data, the Cholesky decomposition of a covariance matrix makes it possible to remove the positive-definiteness constraint and use a generalized linear model setup to jointly model the mean and covariance using covariates (Pourahmadi, 2000). However, this approach may not be directly applicable when the longitudinal data are unbalanced, as coherent regression models for the dependence across all times and subjects may not exist. Within the existing generalized linear model framework, we show how to overcome this and other challenges by embedding the covariance matrix of the observed data for each subject in a larger covariance matrix and employing the familiar EM algorithm to compute the maximum likelihood estimates of the parameters and their standard errors. We illustrate and assess the methodology using real data sets and simulations. © 2011 Elsevier B.V.

  15. EXISTENCE AND ALGORITHM OF SOLUTIONS FOR GENERALIZED STRONGLY MIXED IMPLICIT QUASI-VARIATIONAL INEQUALITIES

    Institute of Scientific and Technical Information of China (English)

    ZENG Luchuan

    2004-01-01

    The purpose of this paper is to introduce and study a new class of generalized strongly mixed implicit quasi-variational inequalities in Hilbert spaces, which includes the known class of generalized mixed implicit quasi-variational inequalities as a special case.By applying the auxiliary variational principle technique, the existence of solutions for this class of quasi-variational inequalities is proved. Moreover, a new iterative algorithm for computing approximate solutions is constructed and the convergence criteria for this iterative algorithm are also established.

  16. A review of linear response theory for general differentiable dynamical systems

    Science.gov (United States)

    Ruelle, David

    2009-04-01

    The classical theory of linear response applies to statistical mechanics close to equilibrium. Away from equilibrium, one may describe the microscopic time evolution by a general differentiable dynamical system, identify nonequilibrium steady states (NESS) and study how these vary under perturbations of the dynamics. Remarkably, it turns out that for uniformly hyperbolic dynamical systems (those satisfying the 'chaotic hypothesis'), the linear response away from equilibrium is very similar to the linear response close to equilibrium: the Kramers-Kronig dispersion relations hold, and the fluctuation-dispersion theorem survives in a modified form (which takes into account the oscillations around the 'attractor' corresponding to the NESS). If the chaotic hypothesis does not hold, two new phenomena may arise. The first is a violation of linear response in the sense that the NESS does not depend differentiably on parameters (but this nondifferentiability may be hard to see experimentally). The second phenomenon is a violation of the dispersion relations: the susceptibility has singularities in the upper half complex plane. These 'acausal' singularities are actually due to 'energy nonconservation': for a small periodic perturbation of the system, the amplitude of the linear response is arbitrarily large. This means that the NESS of the dynamical system under study is not 'inert' but can give energy to the outside world. An 'active' NESS of this sort is very different from an equilibrium state, and it would be interesting to see what happens for active states to the Gallavotti-Cohen fluctuation theorem.

  17. Convergence analysis for general linear methods applied to stiff delay differential equations

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    For Runge-Kutta methods applied to stiff delay differential equations (DDEs), the concept of D-convergence was proposed, which is an extension to that of B-convergence in ordinary differential equations (ODEs). In this paper, D-convergence of general linear methods is discussed and the previous related results are improved. Some order results to determine D-convergence of the methods are obtained.

  18. ASYMPTOTIC NORMALITY OF QUASI MAXIMUM LIKELIHOOD ESTIMATE IN GENERALIZED LINEAR MODELS

    Institute of Scientific and Technical Information of China (English)

    YUE LI; CHEN XIRU

    2005-01-01

    For the Generalized Linear Model (GLM), under some conditions including that the specification of the expectation is correct, it is shown that the Quasi Maximum Likelihood Estimate (QMLE) of the parameter-vector is asymptotic normal. It is also shown that the asymptotic covariance matrix of the QMLE reaches its minimum (in the positive-definte sense) in case that the specification of the covariance matrix is correct.

  19. Damping of a system of linear oscillators using the generalized dry friction

    OpenAIRE

    Ovseevich, Alexander; Fedorov, Aleksey

    2015-01-01

    The problem of damping a system of linear oscillators is considered. The problem is solved by using a control in the form of dry friction. The motion of the system under the control is governed by a system of differential equations with discontinuous right-hand side. A uniqueness and continuity theorem is proved for the phase flow of this system. Thus, the control in the form of generalized dry friction defines the motion of the system of oscillators uniquely.

  20. Representations of general linear groups and categorical actions of Kac-Moody algebras

    OpenAIRE

    Losev, Ivan

    2012-01-01

    This is an expanded version of the lectures given by the author on the 3rd school "Lie algebras, algebraic groups and invariant theory" in Togliatti, Russia. In these notes we explain the concept of a categorical Kac-Moody action by studying an example of the category of rational representations of a general linear group in positive characteristic. We also deal with some more advanced topics: a categorical action on the polynomial representations and crystals of categorical actions.

  1. An Entropy-Based Approach to Path Analysis of Structural Generalized Linear Models: A Basic Idea

    Directory of Open Access Journals (Sweden)

    Nobuoki Eshima

    2015-07-01

    Full Text Available A path analysis method for causal systems based on generalized linear models is proposed by using entropy. A practical example is introduced, and a brief explanation of the entropy coefficient of determination is given. Direct and indirect effects of explanatory variables are discussed as log odds ratios, i.e., relative information, and a method for summarizing the effects is proposed. The example dataset is re-analyzed by using the method.

  2. An Average Linear Difference Scheme for the Generalized Rosenau-KdV Equation

    Directory of Open Access Journals (Sweden)

    Maobo Zheng

    2014-01-01

    Full Text Available An average linear finite difference scheme for the numerical solution of the initial-boundary value problem of Generalized Rosenau-KdV equation is proposed. The existence, uniqueness, and conservation for energy of the difference solution are proved by the discrete energy norm method. It is shown that the finite difference scheme is 2nd-order convergent and unconditionally stable. Numerical experiments verify that the theoretical results are right and the numerical method is efficient and reliable.

  3. Solution to the Generalized Champagne Problem on simultaneous stabilization of linear systems

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The well-known Generalized Champagne Problem on simultaneous stabilization of linear systems is solved by using complex analysis and Blondel's technique. We give a complete answer to the open problem proposed by Patel et al., which automatically includes the solution to the original Champagne Problem. Based on the recent development in automated inequality-type theorem proving, a new stabilizing controller design method is established. Our numerical examples significantly improve the relevant results in the literature.

  4. A proposed experimental platform for measuring the properties of warm dense mixtures: Testing the applicability of the linear mixing model

    Science.gov (United States)

    Hawreliak, James

    2017-06-01

    This paper presents a proposed experimental technique for investigating the impact of chemical interactions in warm dense liquid mixtures. It uses experimental equation of state (EOS) measurements of warm dense liquid mixtures with different compositions to determine the deviation from the linear mixing model. Statistical mechanics is used to derive the EOS of a mixture with a constant pressure linear mixing term (Amagat's rule) and an interspecies interaction term. A ratio between the particle density of two different compositions of mixtures, K(P, T)i: ii, is defined. By comparing this ratio for a range of mixtures, the impact of interspecies interactions can be studied. Hydrodynamic simulations of mixtures with different carbon/hydrogen ratios are used to demonstrate the application of this proposed technique to multiple shock and ramp compression experiments. The limit of the pressure correction that can be measured due to interspecies interactions using this methodology is determined by the uncertainty in the density measurement.

  5. Second degree generalized Jacobi iteration method for solving system of linear equations

    Directory of Open Access Journals (Sweden)

    Tesfaye Kebede Enyew

    2016-05-01

    Full Text Available In this paper, a Second degree generalized Jacobi Iteration method for solving system of linear equations, $Ax=b$ and discuss about the optimal values $a_{1}$ and $b_{1}$ in terms of spectral radius about for the convergence of SDGJ method of $x^{(n+1}=b_{1}[D_{m}^{-1}(L_{m}+U_{m}x^{(n}+k_{1m}]-a_{1}x^{(n-1}.$ Few numerical examples are considered to show that the effective of the Second degree Generalized Jacobi Iteration method (SDGJ in comparison with FDJ, FDGJ, SDJ.

  6. LINEAR LAYER AND GENERALIZED REGRESSION COMPUTATIONAL INTELLIGENCE MODELS FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE

    Directory of Open Access Journals (Sweden)

    S. Goyal

    2012-03-01

    Full Text Available This paper highlights the significance of computational intelligence models for predicting shelf life of processed cheese stored at 7-8 g.C. Linear Layer and Generalized Regression models were developed with input parameters: Soluble nitrogen, pH, Standard plate count, Yeast & mould count, Spores, and sensory score as output parameter. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash - Sutcliffo Coefficient were used in order to compare the prediction ability of the models. The study revealed that Generalized Regression computational intelligence models are quite effective in predicting the shelf life of processed cheese stored at 7-8 g.C.

  7. Interactions in Generalized Linear Models: Theoretical Issues and an Application to Personal Vote-Earning Attributes

    Directory of Open Access Journals (Sweden)

    Tsung-han Tsai

    2013-05-01

    Full Text Available There is some confusion in political science, and the social sciences in general, about the meaning and interpretation of interaction effects in models with non-interval, non-normal outcome variables. Often these terms are casually thrown into a model specification without observing that their presence fundamentally changes the interpretation of the resulting coefficients. This article explains the conditional nature of reported coefficients in models with interactions, defining the necessarily different interpretation required by generalized linear models. Methodological issues are illustrated with an application to voter information structured by electoral systems and resulting legislative behavior and democratic representation in comparative politics.

  8. Invariance of the generalized oscillator under a linear transformation of the related system of orthogonal polynomials

    Science.gov (United States)

    Borzov, V. V.; Damaskinsky, E. V.

    2017-02-01

    We consider the families of polynomials P = { P n ( x)} n=0 ∞ and Q = { Q n ( x)} n=0 ∞ orthogonal on the real line with respect to the respective probability measures μ and ν. We assume that { Q n ( x)} n=0 ∞ and { P n ( x)} n=0 ∞ are connected by linear relations. In the case k = 2, we describe all pairs (P,Q) for which the algebras A P and A Q of generalized oscillators generated by { Qn(x)} n=0 ∞ and { Pn(x)} n=0 ∞ coincide. We construct generalized oscillators corresponding to pairs (P,Q) for arbitrary k ≥ 1.

  9. Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

    Directory of Open Access Journals (Sweden)

    Mingwu Jin

    2012-01-01

    Full Text Available Local canonical correlation analysis (CCA is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM, a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

  10. Linear mixed-effects models for within-participant psychology experiments: an introductory tutorial and free, graphical user interface (LMMgui)

    OpenAIRE

    Magezi, David A.

    2015-01-01

    Linear mixed-effects models (LMMs) are increasingly being used for data analysis in cognitive neuroscience and experimental psychology, where within-participant designs are common. The current article provides an introductory review of the use of LMMs for within-participant data analysis and describes a free, simple, graphical user interface (LMMgui). LMMgui uses the package lme4 (Bates et al., 2014a,b) in the statistical environment R (R Core Team).

  11. Linear mixed-effects models for within-participant psychology experiments: an introductory tutorial and free, graphical user interface (LMMgui).

    Science.gov (United States)

    Magezi, David A

    2015-01-01

    Linear mixed-effects models (LMMs) are increasingly being used for data analysis in cognitive neuroscience and experimental psychology, where within-participant designs are common. The current article provides an introductory review of the use of LMMs for within-participant data analysis and describes a free, simple, graphical user interface (LMMgui). LMMgui uses the package lme4 (Bates et al., 2014a,b) in the statistical environment R (R Core Team).

  12. Benefits of Non-Linear Mixed Effect Modeling and Optimal Design : Pre-Clinical and Clinical Study Applications

    OpenAIRE

    Ernest II, Charles Steven

    2013-01-01

    Despite the growing promise of pharmaceutical research, inferior experimentation or interpretation of data can inhibit breakthrough molecules from finding their way out of research institutions and reaching patients. This thesis provides evidence that better characterization of pre-clinical and clinical data can be accomplished using non-linear mixed effect modeling (NLMEM) and more effective experiments can be conducted using optimal design (OD).  To demonstrate applicability of NLMEM and OD...

  13. Studies on Mixed Slab-Toroidal Electron Temperature Gradient Mode Instabilities in the Columbia Linear Machine

    Science.gov (United States)

    Balbaky, Abed

    This thesis investigates the behavior of electron temperature gradient (ETG) driven instabilities in the Columbia Linear Machine (CLM). Building on prior work in CLM, the primary goal of this research is to produce, identify, and illuminate the basic physics of these instabilities, and explore the behavior of these instabilities under the presence of trapping and curved magnetic field lines. The first part of this thesis is focused on studying the saturated ETG mode, and the general behavior of the mode under varying levels of magnetic curvature. Measuring ETG modes can be problematic since they have large real frequencies, fast growth rates (~MHz) and small spatial scales, but carefully designed probe diagnostics can overcome these limits. In order to produce curved magnetic field lines, we modified CLM to operate with an internal movable mirror coil. We determined the temperature and density profiles under varying curvature, and measured changes in the mode structure and frequency. We found small changes in the azimuthal/poloidal structure and frequency, characterized by an increase in the m-number (mslab˜10-13 and Deltam˜1), along with small changes in the axial/toroidal structure (k∥∥, curvature reactors, where these is a continued push for energy efficiency. A specially designed triple probe has been developed, which can measure fluctuations in temperature and potential simultaneously, with a high frequency and special resolution suitable for ETG studies. We present an experimental scaling of radial transport as a function of magnetic field curvature, again one of the first of its kind. Our findings indicate a modest increase in radial transport (˜2x) with increased curvature, but unlike saturated mode amplitudes, we find that radial transport saturates for higher levels of curvature in CLM.

  14. An A Posteriori Error Analysis of Mixed Finite Element Galerkin Approximations to Second Order Linear Parabolic Problems

    KAUST Repository

    Memon, Sajid

    2012-01-01

    In this article, a posteriori error estimates are derived for mixed finite element Galerkin approximations to second order linear parabolic initial and boundary value problems. Using mixed elliptic reconstructions, a posteriori error estimates in L∞(L2)- and L2(L2)-norms for the solution as well as its flux are proved for the semidiscrete scheme. Finally, based on a backward Euler method, a completely discrete scheme is analyzed and a posteriori error bounds are derived, which improves upon earlier results on a posteriori estimates of mixed finite element approximations to parabolic problems. Results of numerical experiments verifying the efficiency of the estimators have also been provided. © 2012 Society for Industrial and Applied Mathematics.

  15. Sample Sizes Required to Detect Interactions between Two Binary Fixed-Effects in a Mixed-Effects Linear Regression Model.

    Science.gov (United States)

    Leon, Andrew C; Heo, Moonseong

    2009-01-15

    Mixed-effects linear regression models have become more widely used for analysis of repeatedly measured outcomes in clinical trials over the past decade. There are formulae and tables for estimating sample sizes required to detect the main effects of treatment and the treatment by time interactions for those models. A formula is proposed to estimate the sample size required to detect an interaction between two binary variables in a factorial design with repeated measures of a continuous outcome. The formula is based, in part, on the fact that the variance of an interaction is fourfold that of the main effect. A simulation study examines the statistical power associated with the resulting sample sizes in a mixed-effects linear regression model with a random intercept. The simulation varies the magnitude (Δ) of the standardized main effects and interactions, the intraclass correlation coefficient (ρ ), and the number (k) of repeated measures within-subject. The results of the simulation study verify that the sample size required to detect a 2 × 2 interaction in a mixed-effects linear regression model is fourfold that to detect a main effect of the same magnitude.

  16. Personnel planning in general practices: development and testing of a skill mix analysis method.

    Science.gov (United States)

    von Eitzen-Strassel, Juliane; Vrijhoef, Hubertus J M; Derckx, Emmy W C C; de Bakker, Dinny H

    2014-09-18

    General practitioners (GPs) have to match patients' demands with the mix of their practice staff's competencies. However, apart from some general principles, there is little guidance on recruiting new staff. The purpose of this study was to develop and test a method which would allow GPs or practice managers to perform a skill mix analysis which would take into account developments in local demand. The method was designed with a stepwise method using different research strategies. Literature review took place to detect available methods that map, predict, or measure patients' demands or needs and to fill the contents of the skill mix analysis. Focus groups and expert interviews were held both during the design process and in the first test stage. Both secondary data analysis as primary data collection took place to fill the contents of the tool. A pilot study in general practices tested the feasibility of the newly-developed method. The skill mix analysis contains both a quantitative and a qualitative part which includes the following sections: (i) an analysis of the current and the expected future demand; (ii) an analysis of the need to adjust skill mix; (iii) an overview about the functions of different provider disciplines; and (iv) a system to assess the input, assumed or otherwise, of each function concerning the 'catching up demand', the connection between supply and demand, and the introduction of new opportunities. The skill mix analysis shows an acceptable face and content validity and appears feasible in practice. The skill mix analysis method can be used as a basis to analyze and match, systematically, the demand for care and the supply of practice staff.

  17. Linear and non-linear heart rate metrics for the assessment of anaesthetists' workload during general anaesthesia.

    Science.gov (United States)

    Martin, J; Schneider, F; Kowalewskij, A; Jordan, D; Hapfelmeier, A; Kochs, E F; Wagner, K J; Schulz, C M

    2016-12-01

    Excessive workload may impact the anaesthetists' ability to adequately process information during clinical practice in the operation room and may result in inaccurate situational awareness and performance. This exploratory study investigated heart rate (HR), linear and non-linear heart rate variability (HRV) metrics and subjective ratings scales for the assessment of workload associated with the anaesthesia stages induction, maintenance and emergence. HR and HRV metrics were calculated based on five min segments from each of the three anaesthesia stages. The area under the receiver operating characteristics curve (AUC) of the investigated metrics was calculated to assess their ability to discriminate between the stages of anaesthesia. Additionally, a multiparametric approach based on logistic regression models was performed to further evaluate whether linear or non-linear heart rate metrics are suitable for the assessment of workload. Mean HR and several linear and non-linear HRV metrics including subjective workload ratings differed significantly between stages of anaesthesia. Permutation Entropy (PeEn, AUC=0.828) and mean HR (AUC=0.826) discriminated best between the anaesthesia stages induction and maintenance. In the multiparametric approach using logistic regression models, the model based on non-linear heart rate metrics provided a higher AUC compared with the models based on linear metrics. In this exploratory study based on short ECG segment analysis, PeEn and HR seem to be promising to separate workload levels between different stages of anaesthesia. The multiparametric analysis of the regression models favours non-linear heart rate metrics over linear metrics. © The Author 2016. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  18. The Exterior Tricomi Problem for Generalized Mixed Equations with Parabolic Degeneracy

    Institute of Scientific and Technical Information of China (English)

    Guo Chun WEN

    2006-01-01

    This paper deals with the exterior Tricomi problem for generalized mixed equations with parabolic degeneracy. Firstly the representation of solutions of the problem for the equations is given, and then the uniqueness and existence of solutions are proved by a new method.

  19. Unfolding Mixed-Symmetry Fields in AdS and the BMV Conjecture I. General Formalism

    CERN Document Server

    Boulanger, Nicolas; Sundell, Per

    2009-01-01

    We present some generalities of unfolded on-shell dynamics that are useful in analyzing the BMV conjecture for mixed-symmetry fields in constantly curved backgrounds. In particular we discuss the unfolded notion of local degrees of freedom in theories with and without gravity and with and without massive deformation parameters, using the language of Weyl zero-form modules and their duals.

  20. Deriving Internal Energy by Virtue of Generalized Feynman-Hellmann Theorem for Mixed States

    Institute of Scientific and Technical Information of China (English)

    FAN Hong-Yi; JIANG Zhong-Hua

    2005-01-01

    We show how to directly use the generalized Feynman-Hellmann theorem, which is suitable for mixed state ensemble average, to derive the internal energy of Hamiltonian systems. A concrete example, which is a two coupled harminic oscillators, is used for elucidating our approach.

  1. LETTER TO THE EDITOR: Mixed population Minority Game with generalized strategies

    Science.gov (United States)

    Jefferies, P.; Hart, M.; Johnson, N. F.; Hui, P. M.

    2000-11-01

    We present a quantitative theory, based on crowd effects, for the market volatility in a Minority Game played by a mixed population. Below a critical concentration of generalized strategy players, we find that the volatility in the crowded regime remains above the random coin-toss value regardless of the `temperature' controlling strategy use. Our theory yields good agreement with numerical simulations.

  2. General Education in Health Science-Focused Institutions: An Explanatory Mixed Methods Study

    Science.gov (United States)

    Rosario, Peggy

    2012-01-01

    The purpose of this study was to describe the structure of general education curricula at baccalaureate colleges of health science in relationship to Bergquist's Career-Based Model of curriculum. Using an explanatory sequential mixed methods approach, the model was tested by examining whether the curricula were both prescriptive and specific.…

  3. Generalized Distributed Network Coding Based on Nonbinary Linear Block Codes for Multi-User Cooperative Communications

    CERN Document Server

    Rebelatto, João Luiz; Li, Yonghui; Vucetic, Branka

    2010-01-01

    In this work, we propose and analyze a generalized construction of distributed network codes for a network consisting of M users sending different information to a common base station through independent block fading channels. The aim is to increase the diversity order of the system without reducing its code rate. The proposed scheme, called generalized dynamic network codes (GDNC), is a generalization of the dynamic network codes (DNC) recently proposed by Xiao and Skoglung. The design of the network codes that maximizes the diversity order is recognized as equivalent to the design of linear block codes over a nonbinary finite field under the Hamming metric. The proposed scheme offers a much better tradeoff between rate and diversity order. An outage probability analysis showing the improved performance is carried out, and computer simulations results are shown to agree with the analytical results.

  4. Bayesian Variable Selection and Computation for Generalized Linear Models with Conjugate Priors.

    Science.gov (United States)

    Chen, Ming-Hui; Huang, Lan; Ibrahim, Joseph G; Kim, Sungduk

    2008-07-01

    In this paper, we consider theoretical and computational connections between six popular methods for variable subset selection in generalized linear models (GLM's). Under the conjugate priors developed by Chen and Ibrahim (2003) for the generalized linear model, we obtain closed form analytic relationships between the Bayes factor (posterior model probability), the Conditional Predictive Ordinate (CPO), the L measure, the Deviance Information Criterion (DIC), the Aikiake Information Criterion (AIC), and the Bayesian Information Criterion (BIC) in the case of the linear model. Moreover, we examine computational relationships in the model space for these Bayesian methods for an arbitrary GLM under conjugate priors as well as examine the performance of the conjugate priors of Chen and Ibrahim (2003) in Bayesian variable selection. Specifically, we show that once Markov chain Monte Carlo (MCMC) samples are obtained from the full model, the four Bayesian criteria can be simultaneously computed for all possible subset models in the model space. We illustrate our new methodology with a simulation study and a real dataset.

  5. Normality of raw data in general linear models: The most widespread myth in statistics

    Science.gov (United States)

    Kery, Marc; Hatfield, Jeff S.

    2003-01-01

    In years of statistical consulting for ecologists and wildlife biologists, by far the most common misconception we have come across has been the one about normality in general linear models. These comprise a very large part of the statistical models used in ecology and include t tests, simple and multiple linear regression, polynomial regression, and analysis of variance (ANOVA) and covariance (ANCOVA). There is a widely held belief that the normality assumption pertains to the raw data rather than to the model residuals. We suspect that this error may also occur in countless published studies, whenever the normality assumption is tested prior to analysis. This may lead to the use of nonparametric alternatives (if there are any), when parametric tests would indeed be appropriate, or to use of transformations of raw data, which may introduce hidden assumptions such as multiplicative effects on the natural scale in the case of log-transformed data. Our aim here is to dispel this myth. We very briefly describe relevant theory for two cases of general linear models to show that the residuals need to be normally distributed if tests requiring normality are to be used, such as t and F tests. We then give two examples demonstrating that the distribution of the response variable may be nonnormal, and yet the residuals are well behaved. We do not go into the issue of how to test normality; instead we display the distributions of response variables and residuals graphically.

  6. The potential in general linear electrodynamics. Causal structure, propagators and quantization

    Energy Technology Data Exchange (ETDEWEB)

    Siemssen, Daniel [Department of Mathematical Methods in Physics, Faculty of Physics, University of Warsaw (Poland); Pfeifer, Christian [Institute for Theoretical Physics, Leibniz Universitaet Hannover (Germany); Center of Applied Space Technology and Microgravity (ZARM), Universitaet Bremen (Germany)

    2016-07-01

    From an axiomatic point of view, the fundamental input for a theory of electrodynamics are Maxwell's equations dF=0 (or F=dA) and dH=J, and a constitutive law H=F, which relates the field strength 2-form F and the excitation 2-form H. In this talk we consider general linear electrodynamics, the theory of electrodynamics defined by a linear constitutive law. The best known application of this theory is the effective description of electrodynamics inside (linear) media (e.g. birefringence). We analyze the classical theory of the electromagnetic potential A before we use methods familiar from mathematical quantum field theory in curved spacetimes to quantize it. Our analysis of the classical theory contains the derivation of retarded and advanced propagators, the analysis of the causal structure on the basis of the constitutive law (instead of a metric) and a discussion of the classical phase space. This classical analysis sets the stage for the construction of the quantum field algebra and quantum states, including a (generalized) microlocal spectrum condition.

  7. A general theory of linear cosmological perturbations: scalar-tensor and vector-tensor theories

    CERN Document Server

    Lagos, Macarena; Ferreira, Pedro G; Noller, Johannes

    2016-01-01

    We present a method for parametrizing linear cosmological perturbations of theories of gravity, around homogeneous and isotropic backgrounds. The method is sufficiently general and systematic that it can be applied to theories with any degrees of freedom (DoFs) and arbitrary gauge symmetries. In this paper, we focus on scalar-tensor and vector-tensor theories, invariant under linear coordinate transformations. In the case of scalar-tensor theories, we use our framework to recover the simple parametrizations of linearized Horndeski and "Beyond Horndeski" theories, and also find higher-derivative corrections. In the case of vector-tensor theories, we first construct the most general quadratic action for perturbations that leads to second-order equations of motion, which propagates two scalar DoFs. Then we specialize to the case in which the vector field is time-like (\\`a la Einstein-Aether gravity), where the theory only propagates one scalar DoF. As a result, we identify the complete forms of the quadratic act...

  8. Generalized linear sampling method for elastic-wave sensing of heterogeneous fractures

    CERN Document Server

    Pourahmadian, Fatemeh; Haddar, Houssem

    2016-01-01

    A theoretical foundation is developed for active seismic reconstruction of fractures endowed with spatially-varying interfacial condition (e.g.~partially-closed fractures, hydraulic fractures). The proposed indicator functional carries a superior localization property with no significant sensitivity to the fracture's contact condition, measurement errors, and illumination frequency. This is accomplished through the paradigm of the $F_\\sharp$-factorization technique and the recently developed Generalized Linear Sampling Method (GLSM) applied to elastodynamics. The direct scattering problem is formulated in the frequency domain where the fracture surface is illuminated by a set of incident plane waves, while monitoring the induced scattered field in the form of (elastic) far-field patterns. The analysis of the well-posedness of the forward problem leads to an admissibility condition on the fracture's (linearized) contact parameters. This in turn contributes toward establishing the applicability of the $F_\\sharp...

  9. Model Checking for a General Linear Model with Nonignorable Missing Covariates

    Institute of Scientific and Technical Information of China (English)

    Zhi-hua SUN; Wai-Cheung IP; Heung WONG

    2012-01-01

    In this paper,we investigate the model checking problem for a general linear model with nonignorable missing covariates.We show that,without any parametric model assumption for the response probability,the least squares method yields consistent estimators for the linear model even if only the complete data are applied.This makes it feasible to propose two testing procedures for the corresponding model checking problem:a score type lack-of-fit test and a test based on the empirical process.The asymptotic properties of the test statistics are investigated.Both tests are shown to have asymptotic power 1 for local alternatives converging to the null at the rate n-(r),0 ≤ (r) < 1/2.Simulation results show that both tests perform satisfactorily.

  10. General Formulations of Finite-field Method Classified by Symmetry for Molecular Linear and Nonlinear Polarizabilities

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The formulations of the finite-field approach to calculate the linear and non-linear optical coefficients mi, aij, bijk and gijkl of a molecular system with different symmetries have been deduced and summarized. The possible choices of the energy sets of the 48 frequent point groups have been optimized and categorized into 11 classes. With the restriction of symmetry operators, a minimum of 9, no more than 21 energy points have to be calculated in order to determine the coefficients, except in the case of the first class to which C1 point group belongs and in which the 34 non-relative energy points selected in our uniform and general scheme are all needed. The symmetric operators that cause some of the tensor components to vanish have been demonstrated as well.

  11. Non-cooperative stochastic differential game theory of generalized Markov jump linear systems

    CERN Document Server

    Zhang, Cheng-ke; Zhou, Hai-ying; Bin, Ning

    2017-01-01

    This book systematically studies the stochastic non-cooperative differential game theory of generalized linear Markov jump systems and its application in the field of finance and insurance. The book is an in-depth research book of the continuous time and discrete time linear quadratic stochastic differential game, in order to establish a relatively complete framework of dynamic non-cooperative differential game theory. It uses the method of dynamic programming principle and Riccati equation, and derives it into all kinds of existence conditions and calculating method of the equilibrium strategies of dynamic non-cooperative differential game. Based on the game theory method, this book studies the corresponding robust control problem, especially the existence condition and design method of the optimal robust control strategy. The book discusses the theoretical results and its applications in the risk control, option pricing, and the optimal investment problem in the field of finance and insurance, enriching the...

  12. Galaxy Bias and non-Linear Structure Formation in General Relativity

    CERN Document Server

    Baldauf, Tobias; Senatore, Leonardo; Zaldarriaga, Matias

    2011-01-01

    Length scales probed by large scale structure surveys are becoming closer to the horizon scale. Further, it has been recently understood that non-Gaussianity in the initial conditions could show up in a scale dependence of the bias of galaxies at the largest distances. It is therefore important to include General Relativistic effects. Here we provide a General Relativistic generalization of the bias, valid both for Gaussian and non-Gaussian initial conditions. The collapse of objects happens on very small scales, while long-wavelength modes are always in the quasi linear regime. Around every collapsing region, it is therefore possible to find a reference frame that is valid for all times and where the space time is almost flat: the Fermi frame. Here the Newtonian approximation is applicable and the equations of motion are the ones of the N-body codes. The effects of long-wavelength modes are encoded in the mapping from the cosmological frame to the local frame. For the linear bias, the effect of the long-wave...

  13. Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

    Directory of Open Access Journals (Sweden)

    Xu Hao

    Full Text Available A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb. Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1], a combination of first-order autoregressive and moving average structures [ARMA(1,1], and the compound symmetry structure (CS. Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR, the root mean square error (RMSE, and the adjusted coefficient of determination (adj-R2. For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

  14. A General Linear Wave Theory for Water Waves Propagating over Uneven Porous Bottoms

    Institute of Scientific and Technical Information of China (English)

    锁要红; 黄虎

    2004-01-01

    Starting from the widespread phenomena of porous bottoms in the near shore region, considering fully the diversity of bottom topography and wave number variation, and including the effect of evanescent modes, a general linear wave theory for water waves propagating over uneven porous bottoms in the near shore region is established by use of Green's second identity. This theory can be reduced to a number of the most typical mild-slope equations currently in use and provide a reliable research basis for follow-up development of nonlinear water wave theory involving porous bottoms.

  15. Rate of strong consistency of quasi maximum likelihood estimate in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    YUE Li; CHEN Xiru

    2004-01-01

    Under the assumption that in the generalized linear model (GLM) the expectation of the response variable has a correct specification and some other smooth conditions,it is shown that with probability one the quasi-likelihood equation for the GLM has a solution when the sample size n is sufficiently large. The rate of this solution tending to the true value is determined. In an important special case, this rate is the same as specified in the LIL for iid partial sums and thus cannot be improved anymore.

  16. ASYMPTOTIC NORMALITY OF MAXIMUM QUASI-LIKELIHOOD ESTIMATORS IN GENERALIZED LINEAR MODELS WITH FIXED DESIGN

    Institute of Scientific and Technical Information of China (English)

    Qibing GAO; Yaohua WU; Chunhua ZHU; Zhanfeng WANG

    2008-01-01

    In generalized linear models with fixed design, under the assumption ~ →∞ and otherregularity conditions, the asymptotic normality of maximum quasi-likelihood estimator (β)n, which is the root of the quasi-likelihood equation with natural link function ∑n/i=1Xi(yi-μ(X1/iβ))=0, is obtained,where λ/-n denotes the minimum eigenvalue of ∑n/i=1XiX/1/i, Xi are bounded p x q regressors, and yi are q × 1 responses.

  17. Robust root clustering for linear uncertain systems using generalized Lyapunov theory

    Science.gov (United States)

    Yedavalli, R. K.

    1993-01-01

    Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

  18. Generalized Preconditioned MHSS Method for a Class of Complex Symmetric Linear Systems

    Directory of Open Access Journals (Sweden)

    Cui-Xia Li

    2014-01-01

    Full Text Available Based on the modified Hermitian and skew-Hermitian splitting (MHSS and preconditioned MHSS (PMHSS methods, a generalized preconditioned MHSS (GPMHSS method for a class of complex symmetric linear systems is presented. Theoretical analysis gives an upper bound for the spectral radius of the iteration matrix. From a practical point of view, we have analyzed and implemented inexact GPMHSS (IGPMHSS iteration, which employs Krylov subspace methods as its inner processes. Numerical experiments are reported to confirm the efficiency of the proposed methods.

  19. An Investigation on the Parabolic Subgroups of the General Linear Groups by Using GAP

    Institute of Scientific and Technical Information of China (English)

    SaadABedaiwi; LIShang-zhi

    2004-01-01

    A typical example for the algebraic groups is the general linear groups G=GL(n,F), we have studied the structure of such groups and paid special attention to its important substructures, namely the Parabolic subgroups. For a given G we computed all the Parabolic subgroups and determined their number, depending on the fact that any finite group has a composition series and the composition factors of a composition series are simple groups which are completely classified, we report here some investigations on the computed Parabolic subgroups. This has been done with the utility of GAP.

  20. Robust root clustering for linear uncertain systems using generalized Lyapunov theory

    Science.gov (United States)

    Yedavalli, R. K.

    1993-01-01

    Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

  1. General mixed problems for the KdV equations on bounded intervals

    Directory of Open Access Journals (Sweden)

    Nikolai A. Larkin

    2010-11-01

    Full Text Available This article is concerned with initial-boundary value problems for the Korteweg-de Vries (KdV equation on bounded intervals. For general linear boundary conditions and small initial data, we prove the existence and uniqueness of global regular solutions and its exponential decay, as $toinfty$.

  2. Healthcare assistants in general practice: practical and conceptual issues of skill-mix change.

    Science.gov (United States)

    Bosley, Sara; Dale, Jeremy

    2008-02-01

    The emergence of healthcare assistants (HCAs) in general practice raises questions about roles and responsibilities, patients' acceptance, cost-effectiveness, patient safety and delegation, training and competence, workforce development, and professional identity. There has been minimal research into the role of HCAs and their experiences, as well as those of other staff working with HCAs in general practice. Lessons may be learned from their role and evidence of their effectiveness in hospital settings. Such research highlights blurred and contested role boundaries and threats to professional identity, which have implications for teamwork, quality of patient care, and patient safety. In this paper it is argued that transferability of evidence from hospital settings to the context of general practice cannot be assumed. Drawing on the limited research in general practice, the challenges and benefits of developing the HCA role in general practice are discussed. It is suggested that in the context of changing skill-mix models, viewing roles as fluid and dynamic is more helpful and reflective of individuals' experiences than endeavouring to impose fixed role boundaries. It is concluded that HCAs can make an increasingly useful contribution to the skill mix in general practice, but that more research and evaluation are needed to inform their training and development within the general practice team.

  3. MULTIGRID METHODS FOR THE GENERALIZED STOKES EQUATIONS BASED ON MIXED FINITE ELEMENT METHODS

    Institute of Scientific and Technical Information of China (English)

    Qing-ping Deng; Xiao-ping Feng

    2002-01-01

    Multigrid methods are developed and analyzed for the generalized stationary Stokes equations which are discretized by various mixed finite element methods. In this paper, the multigrid algorithm, the criterion for prolongation operators and the convergence analysis are all established in an abstract and element-independent fashion. It is proven that the multigrid algorithm converges optimally if the prolongation operator satisfies the criterion.To utilize the abstract result, more than ten well-known mixed finite elements for the Stokes problems are discussed in detail and examples of prolongation operators are constructed explicitly. For nonconforming elements, it is shown that the usual local averaging technique for constructing prolongation operators can be replaced by a computationally cheaper alternative, random choice technique. Moreover, since the algorithm and analysis allows using of nonnested meshes, the abstract result also applies to low order mixed finite elements, which are usually stable only for some special mesh structures.

  4. Vector generalized linear and additive models with an implementation in R

    CERN Document Server

    Yee, Thomas W

    2015-01-01

    This book presents a statistical framework that expands generalized linear models (GLMs) for regression modelling. The framework shared in this book allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. This is possible through the approximately half-a-dozen major classes of statistical models included in the book and the software infrastructure component, which makes the models easily operable.    The book’s methodology and accompanying software (the extensive VGAM R package) are directed at these limitations, and this is the first time the methodology and software are covered comprehensively in one volume. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. The demands of practical data analysis, however, require a flexibility that GLMs do not have. Data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. This book ...

  5. Rigorous asymptotic and moment-preserving diffusion approximations for generalized linear Boltzmann transport in d dimensions

    CERN Document Server

    d'Eon, Eugene

    2013-01-01

    We derive new diffusion solutions to the monoenergetic generalized linear Boltzmann transport equation (GLBE) for the stationary collision density and scalar flux about an isotropic point source in an infinite $d$-dimensional absorbing medium with isotropic scattering. We consider both classical transport theory with exponentially-distributed free paths in arbitrary dimensions as well as a number of non-classical transport theories (non-exponential random flights) that describe a broader class of transport processes within partially-correlated random media. New rigorous asymptotic diffusion approximations are derived where possible. We also generalize Grosjean's moment-preserving approach of separating the first (or uncollided) distribution from the collided portion and approximating only the latter using diffusion. We find that for any spatial dimension and for many free-path distributions Grosjean's approach produces compact, analytic approximations that are, overall, more accurate for high absorption and f...

  6. A general derivation of the subharmonic threshold for non-linear bubble oscillations.

    Science.gov (United States)

    Prosperetti, Andrea

    2013-06-01

    The paper describes an approximate but rather general derivation of the acoustic threshold for a subharmonic component to be possible in the sound scattered by an insonified gas bubble. The general result is illustrated with several specific models for the mechanical behavior of the surface coating of bubbles used as acoustic contrast agents. The approximate results are found to be in satisfactory agreement with fully non-linear numerical results in the literature. The amplitude of the first harmonic is also found by the same method. A fundamental feature identified by the analysis is that the subharmonic threshold can be considerably lowered with respect to that of an uncoated free bubble if the mechanical response of the coating varies rapidly in the neighborhood of certain specific values of the bubble radius, e.g., because of buckling.

  7. Wave packet dynamics in one-dimensional linear and nonlinear generalized Fibonacci lattices.

    Science.gov (United States)

    Zhang, Zhenjun; Tong, Peiqing; Gong, Jiangbin; Li, Baowen

    2011-05-01

    The spreading of an initially localized wave packet in one-dimensional linear and nonlinear generalized Fibonacci (GF) lattices is studied numerically. The GF lattices can be classified into two classes depending on whether or not the lattice possesses the Pisot-Vijayaraghavan property. For linear GF lattices of the first class, both the second moment and the participation number grow with time. For linear GF lattices of the second class, in the regime of a weak on-site potential, wave packet spreading is close to ballistic diffusion, whereas in the regime of a strong on-site potential, it displays stairlike growth in both the second moment and the participation number. Nonlinear GF lattices are then investigated in parallel. For the first class of nonlinear GF lattices, the second moment of the wave packet still grows with time, but the corresponding participation number does not grow simultaneously. For the second class of nonlinear GF lattices, an analogous phenomenon is observed for the weak on-site potential only. For a strong on-site potential that leads to an enhanced nonlinear self-trapping effect, neither the second moment nor the participation number grows with time. The results can be useful in guiding experiments on the expansion of noninteracting or interacting cold atoms in quasiperiodic optical lattices.

  8. Continuous-wave four-wave mixing with linear growth based on electromagnetically dual induced transparency

    Institute of Scientific and Technical Information of China (English)

    Jiahua Li(李家华); Wenxing Yang(杨文星); Jucun Peng(彭菊村)

    2004-01-01

    Using Schrodinger-Maxwell formalism, we propose and analyze a continuous-wave four-wave mixing (FWM) scheme for the generation of coherent light in a six-level atomic system based on electromagnetically dual induced transparency. We derive the corresponding explicit analytical expressions for the generated mixing field. We find that the scheme greatly enhances FWM production efficiency and is also capable of inhibiting and delaying the onset of the detrimental three-photon destructive interference by choosing the proper decay rate in the second electromagnetically induced transparency (EIT) process.In addition, such an optical process also provides possibilities for producing short-wave-length coherent radiation at low pump intensities.

  9. A System of Generalized Mixed Equilibrium Problems, Maximal Monotone Operators, and Fixed Point Problems with Application to Optimization Problems

    Directory of Open Access Journals (Sweden)

    Pongsakorn Sunthrayuth

    2012-01-01

    Full Text Available We introduce a new iterative algorithm for finding a common element of the set of solutions of a system of generalized mixed equilibrium problems, zero set of the sum of a maximal monotone operators and inverse-strongly monotone mappings, and the set of common fixed points of an infinite family of nonexpansive mappings with infinite real number. Furthermore, we prove under some mild conditions that the proposed iterative algorithm converges strongly to a common element of the above four sets, which is a solution of the optimization problem related to a strongly positive bounded linear operator. The results presented in the paper improve and extend the recent ones announced by many others.

  10. On a mixed problem for a linear coupled system with variable coefficients

    Directory of Open Access Journals (Sweden)

    H. R. Clark

    1998-02-01

    Full Text Available We prove existence, uniqueness and exponential decay of solutions to the mixed problem $$u''(x,t-mu(tDelta u(x,t+sum_{i=1}^n {partial hetaoverpartial x_i}(x,t=0 $$ $$ heta'(x,t-Delta heta(x,t +sum_{i=1}^n {partial u'overpartial x_i}(x,t=0,,$$ with a suitable boundary damping, and a positive real-valued function $mu$.

  11. Non-linear composition dependence of the conductivity parameters in alkali halides mixed crystals

    Energy Technology Data Exchange (ETDEWEB)

    Zardas, Georgios E., E-mail: gzardas@phys.uoa.g [Department of Solid State Physics, Faculty of Physics, University of Athens, Panepistimiopolis, 157 84 Zografos (Greece)

    2009-06-01

    Since mixed alkali halides were found to have applications in optical, optoelectronic and electronic devices, a strong interest has recently expressed for the study of their physical properties. Here, we discuss the experimental finding that a maximum conductivity enhancement with respect to pure constituents is obtained at a certain composition. We show that this composition can be predicted from the bulk properties of the end members.

  12. A mixed finite element formulation for a non-linear, transversely isotropic material model for the cardiac tissue.

    Science.gov (United States)

    Thorvaldsen, Tom; Osnes, Harald; Sundnes, Joakim

    2005-12-01

    In this paper we present a mixed finite element method for modeling the passive properties of the myocardium. The passive properties are described by a non-linear, transversely isotropic, hyperelastic material model, and the myocardium is assumed to be almost incompressible. Single-field, pure displacement-based formulations are known to cause numerical difficulties when applied to incompressible or slightly compressible material cases. This paper presents an alternative approach in the form of a mixed formulation, where a separately interpolated pressure field is introduced as a primary unknown in addition to the displacement field. Moreover, a constraint term is included in the formulation to enforce (almost) incompressibility. Numerical results presented in the paper demonstrate the difficulties related to employing a pure displacement-based method, applying a set of physically relevant material parameter values for the cardiac tissue. The same problems are not experienced for the proposed mixed method. We show that the mixed formulation provides reasonable numerical results for compressible as well as nearly incompressible cases, also in situations of large fiber stretches. There is good agreement between the numerical results and the underlying analytical models.

  13. Mixed valence character of anionic linear beryllium chains: a CAS-SCF and MR-CI study.

    Science.gov (United States)

    Pastore, Mariachiara; Monari, Antonio; Evangelisti, Stefano; Leininger, Thierry

    2009-12-31

    A theoretical investigation on the mixed valence behavior, or bistability, of a series of anionic linear chains composed of beryllium atoms is presented. Calculations on Be(N)- (with N = 7, ..., 13) were performed at CAS-SCF and MR-CI levels by using an ANO basis set containing 6s4p3d2f contracted orbitals for each atom. Our results show a consistent gradual shift between different classes of mixed valence compounds as the number of beryllium atoms increases, from strong coupling (class III) toward valence-trapped (class II). Indeed, in the largest cases (N > 10), the anionic chains were found to become asymptotically closer to class I, where the coupling vanishes. The intramolecular electron-transfer parameters V(ab), E(barr), and E(opt) were calculated for each atomic chain. It is shown that the decrease of V(ab) with increasing N follows an exponential pattern.

  14. Comparison Between Linear and Nonlinear Models of Mixed Pixels in Remote Sensing Satellite Images Based on Cierniewski Surface BRDF Model by Means of Monte Carlo Ray Tracing Simulation

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2013-04-01

    Full Text Available Comparative study on linear and nonlinear mixed pixel models of which pixels in remote sensing satellite images is composed with plural ground cover materials mixed together, is conducted for remote sensing satellite image analysis. The mixed pixel models are based on Cierniewski of ground surface reflectance model. The comparative study is conducted by using of Monte Carlo Ray Tracing: MCRT simulations. Through simulation study, the difference between linear and nonlinear mixed pixel models is clarified. Also it is found that the simulation model is validated.

  15. Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification

    Science.gov (United States)

    Spinnato, J.; Roubaud, M.-C.; Burle, B.; Torrésani, B.

    2015-06-01

    Objective. The main goal of this work is to develop a model for multisensor signals, such as magnetoencephalography or electroencephalography (EEG) signals that account for inter-trial variability, suitable for corresponding binary classification problems. An important constraint is that the model be simple enough to handle small size and unbalanced datasets, as often encountered in BCI-type experiments. Approach. The method involves the linear mixed effects statistical model, wavelet transform, and spatial filtering, and aims at the characterization of localized discriminant features in multisensor signals. After discrete wavelet transform and spatial filtering, a projection onto the relevant wavelet and spatial channels subspaces is used for dimension reduction. The projected signals are then decomposed as the sum of a signal of interest (i.e., discriminant) and background noise, using a very simple Gaussian linear mixed model. Main results. Thanks to the simplicity of the model, the corresponding parameter estimation problem is simplified. Robust estimates of class-covariance matrices are obtained from small sample sizes and an effective Bayes plug-in classifier is derived. The approach is applied to the detection of error potentials in multichannel EEG data in a very unbalanced situation (detection of rare events). Classification results prove the relevance of the proposed approach in such a context. Significance. The combination of the linear mixed model, wavelet transform and spatial filtering for EEG classification is, to the best of our knowledge, an original approach, which is proven to be effective. This paper improves upon earlier results on similar problems, and the three main ingredients all play an important role.

  16. Application of spectral linear mixing to rock slabs analyses at various scales using Ma_Miss BreadBoard instrument

    Science.gov (United States)

    De Angelis, Simone; Manzari, Paola; De Sanctis, Maria Cristina; Altieri, Francesca; Carli, Cristian; Agrosì, Giovanna

    2017-09-01

    Focus of this work is the analysis of rock slabs by means of the Ma_Miss BreadBoard instrument. Ma_Miss (Mars Multispectral Imager for Subsurface Studies, Coradini et al., 2001; De Sanctis et al., 2017) is the miniaturized imaging spectrometer onboard the ESA Exomars 2020 mission. Here we report the results of the analysis carried out on rock slabs using the Ma_Miss breadboard (BB) (De Angelis et al., 2014, 2015) and a Spectro-Goniometer (SPG). The samples are three volcanic rocks (from the Aeolian Islands and Montiferru volcanoes, Italy) and two carbonate rocks (from Central Apennines, Italy). Visible and near infrared spectroscopic characterization has been first performed on all the samples with a Spectro-goniometer (SPG). Successively, higher spatial resolution spectra were acquired with the Ma_Miss BB setup in each of the areas analyzed with the SPG. We compared the spectra of the same areas of the slabs, acquired with SPG and Ma_Miss BB. Three different analysis approaches have been performed on the spectra: arithmetical averaging of the spectra, linear mixing of reflectances and linear mixing of Single Scattering Albedoes (using Hapke model). The comparison shows that: (i) Ma_Miss instrument has great capabilities for the investigation of rock surfaces with high detail; a large number of different mineralogical phases can be recognized thanks to Ma_Miss high resolution within each millimeter-sized analyzed area; (ii) the agreement with SPG spectra is excellent especially when linear mixing is applied for the convolution of Ma_Miss BB spectra.

  17. Blended General Linear Methods based on Boundary Value Methods in the GBDF family

    CERN Document Server

    Brugnano, Luigi

    2010-01-01

    Among the methods for solving ODE-IVPs, the class of General Linear Methods (GLMs) is able to encompass most of them, ranging from Linear Multistep Formulae (LMF) to RK formulae. Moreover, it is possible to obtain methods able to overcome typical drawbacks of the previous classes of methods. For example, order barriers for stable LMF and the problem of order reduction for RK methods. Nevertheless, these goals are usually achieved at the price of a higher computational cost. Consequently, many efforts have been made in order to derive GLMs with particular features, to be exploited for their efficient implementation. In recent years, the derivation of GLMs from particular Boundary Value Methods (BVMs), namely the family of Generalized BDF (GBDF), has been proposed for the numerical solution of stiff ODE-IVPs. In particular, this approach has been recently developed, resulting in a new family of L-stable GLMs of arbitrarily high order, whose theory is here completed and fully worked-out. Moreover, for each one o...

  18. Thermodynamic bounds and general properties of optimal efficiency and power in linear responses.

    Science.gov (United States)

    Jiang, Jian-Hua

    2014-10-01

    We study the optimal exergy efficiency and power for thermodynamic systems with an Onsager-type "current-force" relationship describing the linear response to external influences. We derive, in analytic forms, the maximum efficiency and optimal efficiency for maximum power for a thermodynamic machine described by a N×N symmetric Onsager matrix with arbitrary integer N. The figure of merit is expressed in terms of the largest eigenvalue of the "coupling matrix" which is solely determined by the Onsager matrix. Some simple but general relationships between the power and efficiency at the conditions for (i) maximum efficiency and (ii) optimal efficiency for maximum power are obtained. We show how the second law of thermodynamics bounds the optimal efficiency and the Onsager matrix and relate those bounds together. The maximum power theorem (Jacobi's Law) is generalized to all thermodynamic machines with a symmetric Onsager matrix in the linear-response regime. We also discuss systems with an asymmetric Onsager matrix (such as systems under magnetic field) for a particular situation and we show that the reversible limit of efficiency can be reached at finite output power. Cooperative effects are found to improve the figure of merit significantly in systems with multiply cross-correlated responses. Application to example systems demonstrates that the theory is helpful in guiding the search for high performance materials and structures in energy researches.

  19. Generalised linear mixed models analysis of risk factors for contamination of Danish broiler flocks with Salmonella typhimurium

    DEFF Research Database (Denmark)

    Chriél, Mariann; Stryhn, H.; Dauphin, G.

    1999-01-01

    of rearing, and the sampling method are significant. Epidemiological control would seem most efficient on starting at the top levels of the production hierarchy from which a major part of the ST contamination is derived. A secondary purpose of the study is to evaluate different statistical approaches...... and software for the analysis of a moderately-sized data set of veterinary origin. We compare the results from five analyses of the generalised linear mixed model (GLMM) type. The first observation is that the results agree reasonably well and lead to similar conclusions. A closer look reveals certain patterns...

  20. A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing

    DEFF Research Database (Denmark)

    Fischetti, Martina; Leth, John-Josef; Borchersen, Anders Bech

    2015-01-01

    A Mixed-Integer Linear Programming (MILP) approach is proposed to optimize the turbine allocation and inter-array offshore cable routing. The two problems are considered with a two steps strategy, solving the layout problem first and then the cable problem. We give an introduction to both problems...... and present the MILP models we developed to solve them. To deal with interference in the onshore cases, we propose an adaptation of the standard Jensen’s model, suitable for 3D cases. A simple Stochastic Programming variant of our model allows us to consider different wind scenarios in the optimization...

  1. An Application of the Multivariate Linear Mixed Model to the Analysis of Shoulder Complexity in Breast Cancer Patients

    Directory of Open Access Journals (Sweden)

    Gholamreza Oskrochi

    2016-03-01

    Full Text Available In this study, four major muscles acting on the scapula were investigated in patients who had been treated in the last six years for unilateral carcinoma of the breast. Muscle activity was assessed by electromyography during abduction and adduction of the affected and unaffected arms. The main principal aim of the study was to compare shoulder muscle activity in the affected and unaffected shoulder during elevation of the arm. A multivariate linear mixed model was introduced and applied to address the principal aims. The result of fitting this model to the data shows a huge improvement as compared to the alternatives.

  2. Suppression of chaos at slow variables by rapidly mixing fast dynamics through linear energy-preserving coupling

    CERN Document Server

    Abramov, Rafail V

    2011-01-01

    Chaotic multiscale dynamical systems are common in many areas of science, one of the examples being the interaction of the slow climate dynamics with the fast turbulent weather dynamics. One of the key questions about chaotic multiscale systems is how the fast dynamics affects chaos at the slow variables, and, therefore, impacts uncertainty and predictability of the slow dynamics. Here we demonstrate that the linear slow-fast coupling with the total energy conservation property promotes the suppression of chaos at the slow variables through the rapid mixing at the fast variables, both theoretically and through numerical simulations. A suitable mathematical framework is developed, connecting the slow dynamics on the tangent subspaces to the infinite-time linear response of the mean state to a constant external forcing at the fast variables. Additionally, it is shown that the uncoupled dynamics for the slow variables may remain chaotic while the complete multiscale system loses chaos and becomes completely pred...

  3. Interference and non-linear properties of four-wave mixing resonances in thermal vapor: analytical results and experimental verification

    CERN Document Server

    Parniak, Michał

    2014-01-01

    We develop a model to calculate non-linear polarization in a non-degenerrate four-wave mixing in diamond configuration which includes the effects of hyperfine structure and Doppler broadening. We verify it against the experiment with $5^{2}S_{1/2}$, $5^{2}P_{3/2}$, $5^{2}D_{3/2}$ and $5^{2}P_{1/2}$ levels of rubidium 85. Uncomplicated algebra enables us to express the non-linear susceptibility of a thermal ensemble in low intensity regime in terms of Voight-like profiles and conforms precisely with the experiment. The agreement is also satisfactory at high intensity and the analytical model correctly predicts the position and shape of resonances. Our intelligible results elucidate the physics of coherent interaction of light with atoms involving higher excited levels in vapors at room temperature, which is used in an increasing range of applications.

  4. On the Generalization of the Timoshenko Beam Model Based on the Micropolar Linear Theory: Static Case

    Directory of Open Access Journals (Sweden)

    Andrea Nobili

    2015-01-01

    Full Text Available Three generalizations of the Timoshenko beam model according to the linear theory of micropolar elasticity or its special cases, that is, the couple stress theory or the modified couple stress theory, recently developed in the literature, are investigated and compared. The analysis is carried out in a variational setting, making use of Hamilton’s principle. It is shown that both the Timoshenko and the (possibly modified couple stress models are based on a microstructural kinematics which is governed by kinosthenic (ignorable terms in the Lagrangian. Despite their difference, all models bring in a beam-plane theory only one microstructural material parameter. Besides, the micropolar model formally reduces to the couple stress model upon introducing the proper constraint on the microstructure kinematics, although the material parameter is generally different. Line loading on the microstructure results in a nonconservative force potential. Finally, the Hamiltonian form of the micropolar beam model is derived and the canonical equations are presented along with their general solution. The latter exhibits a general oscillatory pattern for the microstructure rotation and stress, whose behavior matches the numerical findings.

  5. Chlorophyll modulation of mixed layer thermodynamics in a mixed-layer isopycnal general circulation model - An example from Arabian Sea and Equatorial Pacific

    Digital Repository Service at National Institute of Oceanography (India)

    Nakamoto, S.; PrasannaKumar, S.; Oberhuber, J.M.; Saito, H.; Muneyama, K.

    in the ocean isopycnal general circulation model (OPYC). A higher abundance of chlorophyll increases absorption of solar irradiance and heating rate in the upper ocean, resulting in decreasing the mixed layer thickness than they would be under clear waer...

  6. Mixed brush made of 4-arm stars and linear chains: MD simulations

    Science.gov (United States)

    Su, Chan-Fei; Merlitz, Holger; Wu, Chen-Xu; Sommer, Jens-Uwe

    2016-12-01

    We investigate the structural properties of binary polymer brushes, composed of functional 4-armed star polymers and chemically identical linear polymers of different molecular weights. The molecular dynamics simulations confirm recent self-consistent field studies, in which a considerable potential of these systems for the design of switchable surfaces has been claimed. The length of the linear chains serves as a control parameter, which, while passing over a critical value, induces a sharp transition of the molecular conformation. We investigate these transitions at different grafting densities and summarize our findings in a phase diagram. The temperature dependence of the brush structure is investigated in a non-selective solvent, and non-trivial variations of the surface composition are observed. The quantity of these latter effects would be insufficient to build switchable systems, and we argue that a minor quantity of solvent selectivity would suffice to enable the desired feature of an environment-responsive coating.

  7. A branch-and-cut-and-price algorithm for the mixed capacitated general routing problem

    DEFF Research Database (Denmark)

    Bach, Lukas; Wøhlk, Sanne; Lysgaard, Jens

    2016-01-01

    In this paper, we consider the Mixed Capacitated General Routing Problem which is a combination of the Capacitated Vehicle Routing Problem and the Capacitated Arc Routing Problem. The problem is also known as the Node, Edge, and Arc Routing Problem. We propose a Branch-and-Cut-and-Price algorithm...... for obtaining optimal solutions to the problem and present computational results based on a set of standard benchmark instances....

  8. Minimum-time control of systems with Coloumb friction: Near global optima via mixed integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    DRIESSEN,BRIAN; SADEGH,NADER

    2000-04-25

    This work presents a method of finding near global optima to minimum-time trajectory generation problem for systems that would be linear if it were not for the presence of Coloumb friction. The required final state of the system is assumed to be maintainable by the system, and the input bounds are assumed to be large enough so that they can overcome the maximum static Coloumb friction force. Other than the previous work for generating minimum-time trajectories for non redundant robotic manipulators for which the path in joint space is already specified, this work represents, to the best of the authors' knowledge, the first approach for generating near global optima for minimum-time problems involving a nonlinear class of dynamic systems. The reason the optima generated are near global optima instead of exactly global optima is due to a discrete-time approximation of the system (which is usually used anyway to simulate such a system numerically). The method closely resembles previous methods for generating minimum-time trajectories for linear systems, where the core operation is the solution of a Phase I linear programming problem. For the nonlinear systems considered herein, the core operation is instead the solution of a mixed integer linear programming problem.

  9. Taylor series approximation of semi-blind best linear unbiased channel estimates for the general linear model

    OpenAIRE

    Pladdy, Christopher; Nerayanuru, Sreenivasa M.; Fimoff, Mark; Özen, Serdar; Zoltowski, Michael

    2004-01-01

    We present a low complexity approximate method for semi-blind best linear unbiased estimation (BLUE) of a channel impulse response vector (CIR) for a communication system, which utilizes a periodically transmitted training sequence, within a continuous stream of information symbols. The algorithm achieves slightly degraded results at a much lower complexity than directly computing the BLUE CIR estimate. In addition, the inverse matrix required to invert the weighted normal equations to solve ...

  10. Convective mixing in vertically-layered porous media: The linear regime and the onset of convection

    Science.gov (United States)

    Ghorbani, Zohreh; Riaz, Amir; Daniel, Don

    2017-08-01

    We study the effect of permeability heterogeneity on the stability of gravitationally unstable, transient, diffusive boundary layers in porous media. Permeability is taken to vary periodically in the horizontal plane normal to the direction of gravity. In contrast to the situation for vertical permeability variation, the horizontal perturbation structures are multimodal. We therefore use a two-dimensional quasi-steady eigenvalue analysis as well as a complementary initial value problem to investigate the stability behavior in the linear regime, until the onset of convection. We find that thick permeability layers enhance instability compared with thin layers when heterogeneity is increased. On the contrary, for thin layers the instability is weakened progressively with increasing heterogeneity to the extent that the corresponding homogeneous case is more unstable. For high levels of heterogeneity, we find that a small change in the permeability field results in large variations in the onset time of convection, similar to the instability event in the linear regime. However, this trend does not persist unconditionally because of the reorientation of vorticity pairs due to the interaction of evolving perturbation structures with heterogeneity. Consequently, an earlier onset of instability does not necessarily imply an earlier onset of convection. A resonant amplification of instability is observed within the linear regime when the dominant perturbation mode is equal to half the wavenumber of permeability variation. On the other hand, a substantial damping occurs when the perturbation mode is equal to the harmonic and sub-harmonic components of the permeability wavenumber. The phenomenon of such harmonic interactions influences both the onset of instability as well as the onset of convection.

  11. Bayesian quantile regression-based partially linear mixed-effects joint models for longitudinal data with multiple features.

    Science.gov (United States)

    Zhang, Hanze; Huang, Yangxin; Wang, Wei; Chen, Henian; Langland-Orban, Barbara

    2017-01-01

    In longitudinal AIDS studies, it is of interest to investigate the relationship between HIV viral load and CD4 cell counts, as well as the complicated time effect. Most of common models to analyze such complex longitudinal data are based on mean-regression, which fails to provide efficient estimates due to outliers and/or heavy tails. Quantile regression-based partially linear mixed-effects models, a special case of semiparametric models enjoying benefits of both parametric and nonparametric models, have the flexibility to monitor the viral dynamics nonparametrically and detect the varying CD4 effects parametrically at different quantiles of viral load. Meanwhile, it is critical to consider various data features of repeated measurements, including left-censoring due to a limit of detection, covariate measurement error, and asymmetric distribution. In this research, we first establish a Bayesian joint models that accounts for all these data features simultaneously in the framework of quantile regression-based partially linear mixed-effects models. The proposed models are applied to analyze the Multicenter AIDS Cohort Study (MACS) data. Simulation studies are also conducted to assess the performance of the proposed methods under different scenarios.

  12. The heritability of general cognitive ability increases linearly from childhood to young adulthood.

    Science.gov (United States)

    Haworth, C M A; Wright, M J; Luciano, M; Martin, N G; de Geus, E J C; van Beijsterveldt, C E M; Bartels, M; Posthuma, D; Boomsma, D I; Davis, O S P; Kovas, Y; Corley, R P; Defries, J C; Hewitt, J K; Olson, R K; Rhea, S-A; Wadsworth, S J; Iacono, W G; McGue, M; Thompson, L A; Hart, S A; Petrill, S A; Lubinski, D; Plomin, R

    2010-11-01

    Although common sense suggests that environmental influences increasingly account for individual differences in behavior as experiences accumulate during the course of life, this hypothesis has not previously been tested, in part because of the large sample sizes needed for an adequately powered analysis. Here we show for general cognitive ability that, to the contrary, genetic influence increases with age. The heritability of general cognitive ability increases significantly and linearly from 41% in childhood (9 years) to 55% in adolescence (12 years) and to 66% in young adulthood (17 years) in a sample of 11 000 pairs of twins from four countries, a larger sample than all previous studies combined. In addition to its far-reaching implications for neuroscience and molecular genetics, this finding suggests new ways of thinking about the interface between nature and nurture during the school years. Why, despite life's 'slings and arrows of outrageous fortune', do genetically driven differences increasingly account for differences in general cognitive ability? We suggest that the answer lies with genotype-environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part based on their genetic propensities.

  13. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

    KAUST Repository

    Cheng, Guang

    2014-02-01

    We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.

  14. Exact solutions to robust control problems involving scalar hyperbolic conservation laws using Mixed Integer Linear Programming

    KAUST Repository

    Li, Yanning

    2013-10-01

    This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.

  15. Mixed delay-independent/delay-dependent stability of uncertain linear time-delayed systems

    Institute of Scientific and Technical Information of China (English)

    LI Wenlin; DONG Rui

    2004-01-01

    @@ Consider uncertain linear time delay systems described by the following state equation: x(t)=[A0+Δ A0(t)]x(t)+∑ri=1[Ai+ΔAi(t)]x(t-τi).(1) x(t)=(t)t∈[-,0];=maxri=1{τi}(2) where Δ A0(*) and Δ Ai(*)(i=1,…,r) are real matrix functions.Δ Ai(t)=LiFi(t)Ei,ΔA0(t)=L0F0(t)E0, where Li,Ei are known real constant matrices and Fi(t) are unknown real time-varying matrices with Lebesgue measurable elements satisfying ‖Fi(t)‖I,t(i=0,1,…,r). In this note, we develop the methods of robust stability which is dependent on the size of some delays but independent on the size of the others and is based on the solution of linear matrix inequalities.

  16. Linear Growth of Continuous-Wave Four-Wave Mixing with Dual Induced Transparency

    Institute of Scientific and Technical Information of China (English)

    WANG Wen-Yi; LI Jia-Hua

    2005-01-01

    Using Schrodinger-Maxwell formalism, we propose and analyze an optical four-wave mixing (FWM) scheme for the generation of coherent light in a coherent six-level atomic medium based on dual electromagnetically induced transparency (EIT). We show that the significantly enhanced conversion efficiency enabled by ultraslow propagation of pump waves has no direct relationship with the single-photon detuning, which is different from the FWM with a single EIT. The most important feature is that our scheme is also capable of inhibiting and delaying the onset of the detrimental three-photon destructive interference that looks like a recent scheme [Phys. Rev. Lett. 91 (2003) 243902] andmay be used for generating short-wave-length coherent radiation.

  17. Geometric and growth rate tests of General Relativity with recovered linear cosmological perturbations

    CERN Document Server

    Wilson, Michael J

    2016-01-01

    I investigate the consistency of the VIMOS Public Extragalactic Redshift Survey v7 galaxy sample with the expansion history and linear growth rate predicted by General Relativity (GR) and a Planck (2015) cosmology. To do so, I measure the redshift-space power spectrum, which is anisotropic due to both redshift-space distortions (RSD) and the Alcock-Paczynski (AP) effect. In Chapter 6, I place constraints of $f \\sigma_8(0.76) = 0.44 \\pm 0.04$ and $f \\sigma_8(1.05) = 0.28 \\pm 0.08$, which remain consistent with GR at 95% confidence. Marginalising over the anisotropic AP effect degrades the constraints by a factor of three but allows $F_{AP} \\equiv (1+z) D_A H/c$ to be simultaneously constrained. The VIPERS v7 joint-posterior on $(f \\sigma_8, F_{AP})$ shows no compelling deviation from GR. Chapter 7 investigates the inclusion of a simple density transform: `clipping' prior to the RSD analysis. This tackles the root-cause of non-linearity and may extend the validity of perturbation theory. Moreover, this marked s...

  18. Developing minds of tomorrow: exploring students' strategies involved in the generalization of linear patterns

    Directory of Open Access Journals (Sweden)

    Areej IsamBarham

    2011-11-01

    Full Text Available The study investigates students' strategies involved in the generalization of "linear patterns". The study followed thequalitative research approach by conducting task-based interviews with twenty-nine primary second grade students fromdifferent high, intermediate and low ability levels. Results of the study presented several strategies involved in thegeneralization of the patterns including visual, auditory, mental, finger counting, verbal counting, and traditional (paper andpencil strategies. The findings revealed that the type of the assigned pattern (simple or complex and the type of the structureof the pattern itself (increasing or decreasing play a big role for students' strategies involved to either discover the rule of thepattern or to extend it. However, students in early ages could master several skills and choose appropriate procedures to dealwith patterns, which indicate that they could develop their algebraic thinking from early stages. Findings of the study alsorevealed that using different senses, using the idea of coins, using the numbers line, recognizing musical sounds, using concretematerials like fingers, applying different visual and mental strategies, and even applying traditional calculations could helpstudents to work with “linear patterns". It is recommended that teachers introduce different strategies and procedures inteaching patterns to meet the needs of students as different learners, give them the opportunities to develop their thinkingstrategies and explore their thoughts. More research is recommended to explore students' strategies involved in thegeneralization of different kinds of patters at different stages.

  19. On some problems of weak consistency of quasi-maximum likelihood estimates in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    In this paper,we explore some weakly consistent properties of quasi-maximum likelihood estimates(QMLE) concerning the quasi-likelihood equation in=1 Xi(yi-μ(Xiβ)) = 0 for univariate generalized linear model E(y |X) = μ(X’β).Given uncorrelated residuals {ei = Yi-μ(Xiβ0),1 i n} and other conditions,we prove that βn-β0 = Op(λn-1/2) holds,where βn is a root of the above equation,β0 is the true value of parameter β and λn denotes the smallest eigenvalue of the matrix Sn = ni=1 XiXi.We also show that the convergence rate above is sharp,provided independent non-asymptotically degenerate residual sequence and other conditions.Moreover,paralleling to the elegant result of Drygas(1976) for classical linear regression models,we point out that the necessary condition guaranteeing the weak consistency of QMLE is Sn-1→ 0,as the sample size n →∞.

  20. On some problems of weak consistency of quasi-maximum likelihood estimates in generalized linear models

    Institute of Scientific and Technical Information of China (English)

    ZHANG SanGuo; LIAO Yuan

    2008-01-01

    In this paper, we explore some weakly consistent properties of quasi-maximum likelihood estimates(QMLE)concerning the quasi-likelihood equation ∑ni=1 Xi(yi-μ(X1iβ)) =0 for univariate generalized linear model E(y|X) =μ(X1β). Given uncorrelated residuals{ei=Yi-μ(X1iβ0), 1≤i≤n}and other conditions, we prove that (β)n-β0=Op(λ--1/2n)holds, where (β)n is a root of the above equation,β0 is the true value of parameter β and λ-n denotes the smallest eigenvalue of the matrix Sn=Σni=1 XiX1i. We also show that the convergence rate above is sharp, provided independent nonasymptotically degenerate residual sequence and other conditions. Moreover, paralleling to the elegant result of Drygas(1976)for classical linear regression models,we point out that the necessary condition guaranteeing the weak consistency of QMLE is S-1n→0, as the sample size n→∞.

  1. The Potential in General Linear Electrodynamics: Causal Structure, Propagators and Quantization

    CERN Document Server

    Pfeifer, Christian

    2016-01-01

    An axiomatic approach to electrodynamics reveals that Maxwell electrodynamics is just one instance of a variety of theories for which the name electrodynamics is justified. They all have in common that their fundamental input are Maxwell's equations $\\textrm{d} F = 0$ (or $F = \\textrm{d} A$) and $\\textrm{d} H = J$ and a constitutive law $H = \\# F$ which relates the field strength two-form $F$ and the excitation two-form $H$. A local and linear constitutive law defines what is called general linear electrodynamics whose best known application are the effective description of electrodynamics inside media including, e.g., birefringence. We will analyze the classical theory of the electromagnetic potential $A$ before we use methods familiar from mathematical quantum field theory in curved spacetimes to quantize it in a locally covariant way. Our analysis of the classical theory contains the derivation of retarded and advanced propagators, the analysis of the causal structure on the basis of the constitutive law (...

  2. General Explicit Solution of Planar Weakly Delayed Linear Discrete Systems and Pasting Its Solutions

    Directory of Open Access Journals (Sweden)

    Josef Diblík

    2014-01-01

    Full Text Available Planar linear discrete systems with constant coefficients and delays x(k+1=Ax(k+∑l=1n‍Blxl(k-ml are considered where k∈ℤ0∞:={0,1,…,∞}, m1,m2,…,mn are constant integer delays, 0linear differential systems with constant coefficients and special delays when the initially infinite dimensional space of solutions on the initial interval turns (after several steps into a finite dimensional set of solutions. For every possible case, explicit general solutions are constructed and, finally, results on the dimensionality of the space of solutions are obtained.

  3. Tuning, Diagnostics & Data Preparation for Generalized Linear Models Supervised Algorithm in Data Mining Technologies

    Directory of Open Access Journals (Sweden)

    Sachin Bhaskar

    2015-07-01

    Full Text Available Data mining techniques are the result of a long process of research and product development. Large amount of data are searched by the practice of Data Mining to find out the trends and patterns that go beyond simple analysis. For segmentation of data and also to evaluate the possibility of future events, complex mathematical algorithms are used here. Specific algorithm produces each Data Mining model. More than one algorithms are used to solve in best way by some Data Mining problems. Data Mining technologies can be used through Oracle. Generalized Linear Models (GLM Algorithm is used in Regression and Classification Oracle Data Mining functions. For linear modelling, GLM is one the popular statistical techniques. For regression and binary classification, GLM is implemented by Oracle Data Mining. Row diagnostics as well as model statistics and extensive co-efficient statistics are provided by GLM. It also supports confidence bounds.. This paper outlines and produces analysis of GLM algorithm, which will guide to understand the tuning, diagnostics & data preparation process and the importance of Regression & Classification supervised Oracle Data Mining functions and it is utilized in marketing, time series prediction, financial forecasting, overall business planning, trend analysis, environmental modelling, biomedical and drug response modelling, etc.

  4. A generalized fuzzy linear programming approach for environmental management problem under uncertainty.

    Science.gov (United States)

    Fan, Yurui; Huang, Guohe; Veawab, Amornvadee

    2012-01-01

    In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO2) control planning model to identify effective SO2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP and then identify desired policies for SO2-emission control under uncertainty.

  5. Towards downscaling precipitation for Senegal - An approach based on generalized linear models and weather types

    Science.gov (United States)

    Rust, H. W.; Vrac, M.; Lengaigne, M.; Sultan, B.

    2012-04-01

    Changes in precipitation patterns with potentially less precipitation and an increasing risk for droughts pose a threat to water resources and agricultural yields in Senegal. Precipitation in this region is dominated by the West-African Monsoon being active from May to October, a seasonal pattern with inter-annual to decadal variability in the 20th century which is likely to be affected by climate change. We built a generalized linear model for a full spatial description of rainfall in Senegal. The model uses season, location, and a discrete set of weather types as predictors and yields a spatially continuous description of precipitation occurrences and intensities. Weather types have been defined on NCEP/NCAR reanalysis using zonal and meridional winds, as well as relative humidity. This model is suitable for downscaling precipitation, particularly precipitation occurrences relevant for drough risk mapping.

  6. Dynamic Average Consensus and Consensusability of General Linear Multiagent Systems with Random Packet Dropout

    Directory of Open Access Journals (Sweden)

    Wen-Min Zhou

    2013-01-01

    Full Text Available This paper is concerned with the consensus problem of general linear discrete-time multiagent systems (MASs with random packet dropout that happens during information exchange between agents. The packet dropout phenomenon is characterized as being a Bernoulli random process. A distributed consensus protocol with weighted graph is proposed to address the packet dropout phenomenon. Through introducing a new disagreement vector, a new framework is established to solve the consensus problem. Based on the control theory, the perturbation argument, and the matrix theory, the necessary and sufficient condition for MASs to reach mean-square consensus is derived in terms of stability of an array of low-dimensional matrices. Moreover, mean-square consensusable conditions with regard to network topology and agent dynamic structure are also provided. Finally, the effectiveness of the theoretical results is demonstrated through an illustrative example.

  7. Quasi-Maximum Likelihood Estimators in Generalized Linear Models with Autoregressive Processes

    Institute of Scientific and Technical Information of China (English)

    Hong Chang HU; Lei SONG

    2014-01-01

    The paper studies a generalized linear model (GLM) yt=h(xTtβ)+εt, t=1, 2, . . . , n, whereε1=η1,εt=ρεt-1+ηt, t=2,3,...,n, h is a continuous diff erentiable function,ηt’s are independent and identically distributed random errors with zero mean and finite varianceσ 2. Firstly, the quasi-maximum likelihood (QML) estimators ofβ,ρandσ 2 are given. Secondly, under mild conditions, the asymptotic properties (including the existence, weak consistency and asymptotic distribution) of the QML estimators are investigated. Lastly, the validity of method is illuminated by a simulation example.

  8. A Fuzzy Approach Using Generalized Dinkelbach’s Algorithm for Multiobjective Linear Fractional Transportation Problem

    Directory of Open Access Journals (Sweden)

    Nurdan Cetin

    2014-01-01

    Full Text Available We consider a multiobjective linear fractional transportation problem (MLFTP with several fractional criteria, such as, the maximization of the transport profitability like profit/cost or profit/time, and its two properties are source and destination. Our aim is to introduce MLFTP which has not been studied in literature before and to provide a fuzzy approach which obtain a compromise Pareto-optimal solution for this problem. To do this, first, we present a theorem which shows that MLFTP is always solvable. And then, reducing MLFTP to the Zimmermann’s “min” operator model which is the max-min problem, we construct Generalized Dinkelbach’s Algorithm for solving the obtained problem. Furthermore, we provide an illustrative numerical example to explain this fuzzy approach.

  9. Bayesian model choice and information criteria in sparse generalized linear models

    CERN Document Server

    Foygel, Rina

    2011-01-01

    We consider Bayesian model selection in generalized linear models that are high-dimensional, with the number of covariates p being large relative to the sample size n, but sparse in that the number of active covariates is small compared to p. Treating the covariates as random and adopting an asymptotic scenario in which p increases with n, we show that Bayesian model selection using certain priors on the set of models is asymptotically equivalent to selecting a model using an extended Bayesian information criterion. Moreover, we prove that the smallest true model is selected by either of these methods with probability tending to one. Having addressed random covariates, we are also able to give a consistency result for pseudo-likelihood approaches to high-dimensional sparse graphical modeling. Experiments on real data demonstrate good performance of the extended Bayesian information criterion for regression and for graphical models.

  10. A New General Linear Convolution Model for fMRI Data Process

    Institute of Scientific and Technical Information of China (English)

    YUAN Hong; CHEN Hua-fu; YAO De-zhong

    2005-01-01

    General linear model (GLM) is the most popular method for functional magnetic resource imaging (fMRI) data analysis. However, its theory is imperfect. The key of this model is how to constitute the design-matrix to model the interesting effects better and separate noises better. For the purpose of detecting brain function activation, according to the principle of GLM, a new convolution model is presented by a new dynamic function convolving with design-matrix, which combining with t-test can be used to detect brain active signal. The fMRI imaging result of visual stimulus experiment indicates that brain activities mainly concentrate among vland v2 areas of visual cortex, and also verified the validity of this technique.

  11. Generalization of the ordinary state-based peridynamic model for isotropic linear viscoelasticity

    Science.gov (United States)

    Delorme, Rolland; Tabiai, Ilyass; Laberge Lebel, Louis; Lévesque, Martin

    2017-02-01

    This paper presents a generalization of the original ordinary state-based peridynamic model for isotropic linear viscoelasticity. The viscoelastic material response is represented using the thermodynamically acceptable Prony series approach. It can feature as many Prony terms as required and accounts for viscoelastic spherical and deviatoric components. The model was derived from an equivalence between peridynamic viscoelastic parameters and those appearing in classical continuum mechanics, by equating the free energy densities expressed in both frameworks. The model was simplified to a uni-dimensional expression and implemented to simulate a creep-recovery test. This implementation was finally validated by comparing peridynamic predictions to those predicted from classical continuum mechanics. An exact correspondence between peridynamics and the classical continuum approach was shown when the peridynamic horizon becomes small, meaning peridynamics tends toward classical continuum mechanics. This work provides a clear and direct means to researchers dealing with viscoelastic phenomena to tackle their problem within the peridynamic framework.

  12. Master equation solutions in the linear regime of characteristic formulation of general relativity

    CERN Document Server

    M., C E Cedeño

    2015-01-01

    From the field equations in the linear regime of the characteristic formulation of general relativity, Bishop, for a Schwarzschild's background, and M\\"adler, for a Minkowski's background, were able to show that it is possible to derive a fourth order ordinary differential equation, called master equation, for the $J$ metric variable of the Bondi-Sachs metric. Once $\\beta$, another Bondi-Sachs potential, is obtained from the field equations, and $J$ is obtained from the master equation, the other metric variables are solved integrating directly the rest of the field equations. In the past, the master equation was solved for the first multipolar terms, for both the Minkowski's and Schwarzschild's backgrounds. Also, M\\"adler recently reported a generalisation of the exact solutions to the linearised field equations when a Minkowski's background is considered, expressing the master equation family of solutions for the vacuum in terms of Bessel's functions of the first and the second kind. Here, we report new sol...

  13. Generalized anxiety and mixed anxiety-depression: association with disability and health care utilization.

    Science.gov (United States)

    Roy-Byrne, P P

    1996-01-01

    Generalized anxiety and mixed anxiety-depression have received less attention than the major mood and anxiety disorders ith respect to their possible effects in increasing disability and health care utilization. A review of recent studies, however, indicates that these conditions are prevalent in primary care medical settings and are associated with significant social and occupational disability. Generalized anxiety disorder is also one of the most common diagnoses seen in patients presenting with medically unexplained somatic complaints such as chest pain, irritable bowel symptoms, and hyperventilation and in patients prone to overutilize health care services in general. It is poorly recognized by primary care physicians, possibly due to its chronicity, which may limit the ability of symptoms to "stand out" and be easily detected. However, it is disproportionately present in "high utilizer" samples found to be particularly "frustrating" to their physicians and is accompanied by a high rate of personality disorders, suggesting that maladaptive personality traits and styles of interaction in such patients may also contribute to underrecognition of symptoms by primary care physicians. These preliminary associations between generalized anxiety disorder/mixed anxiety-depression and both disability and increased health care utilization need to be confirmed with carefully designed and controlled studies.

  14. Dynamic analysis on generalized linear elastic body subjected to large scale rigid rotations

    Institute of Scientific and Technical Information of China (English)

    刘占芳; 颜世军; 符志

    2013-01-01

    The dynamic analysis of a generalized linear elastic body undergoing large rigid rotations is investigated. The generalized linear elastic body is described in kine-matics through translational and rotational deformations, and a modified constitutive relation for the rotational deformation is proposed between the couple stress and the curvature tensor. Thus, the balance equations of momentum and moment are used for the motion equations of the body. The floating frame of reference formulation is applied to the elastic body that conducts rotations about a fixed axis. The motion-deformation coupled model is developed in which three types of inertia forces along with their incre-ments are elucidated. The finite element governing equations for the dynamic analysis of the elastic body under large rotations are subsequently formulated with the aid of the constrained variational principle. A penalty parameter is introduced, and the rotational angles at element nodes are treated as independent variables to meet the requirement of C1 continuity. The elastic body is discretized through the isoparametric element with 8 nodes and 48 degrees-of-freedom. As an example with an application of the motion-deformation coupled model, the dynamic analysis on a rotating cantilever with two spatial layouts relative to the rotational axis is numerically implemented. Dynamic frequencies of the rotating cantilever are presented at prescribed constant spin velocities. The maximal rigid rotational velocity is extended for ensuring the applicability of the linear model. A complete set of dynamical response of the rotating cantilever in the case of spin-up maneuver is examined, it is shown that, under the ultimate rigid rotational velocities less than the maximal rigid rotational velocity, the stress strength may exceed the material strength tolerance even though the displacement and rotational angle responses are both convergent. The influence of the cantilever layouts on their responses and

  15. Systems of general nonlinear set-valued mixed variational inequalities problems in Hilbert spaces

    Directory of Open Access Journals (Sweden)

    Cho Yeol

    2011-01-01

    Full Text Available Abstract In this paper, the existing theorems and methods for finding solutions of systems of general nonlinear set-valued mixed variational inequalities problems in Hilbert spaces are studied. To overcome the difficulties, due to the presence of a proper convex lower semi-continuous function, φ and a mapping g, which appeared in the considered problem, we have used some applications of the resolvent operator technique. We would like to point out that although many authors have proved results for finding solutions of the systems of nonlinear set-valued (mixed variational inequalities problems, it is clear that it cannot be directly applied to the problems that we have considered in this paper because of φ and g. 2000 AMS Subject Classification: 47H05; 47H09; 47J25; 65J15.

  16. Multivariable Lagrange expansion and generalization of Carlitz-Srivastava mixed generating functions

    Energy Technology Data Exchange (ETDEWEB)

    Dattoli, G. [ENEA, Centro Ricerche Frascati, Rome (Italy). Dipt. Innovazione; Lorenzutta, S. [ENEA, Centro Ricerche Ezio Clementel, Bologna (Italy). Dipt. Innovazione; Sacchetti, D. [Rome Univ. La Sapienza, Rome (Italy). Dipt. di Statistica, Probabilita' e Stat. Applicate

    1999-07-01

    Families of mixed generating functions, generalizing those of the Carlitz-Srivastava type, are derived by exploiting methods based on the multivariable extension of the Lagrange expansion. It is also shown that the combination with techniques of operational nature offers a wide flexibility to explore a wealth of mixed bilateral generating functions for special functions with many variables. [Italian] In questo lavoro si derivano famiglie di funzioni generatrici che generalizzano quelle del tipo Carlitz-Srivastava. I metodi utilizzati sono basati su una estensione a piu' variabili della espansione di Lagrange. Si dimostra anche che una opportuna combinazione con tecniche di natura operatoriale offre un'ampia flessibilita' per lo studio di funzioni generatrici viste per funzioni speciali con piu' variabili.

  17. A mixed integer linear programming model applied in barge planning for Omya

    Directory of Open Access Journals (Sweden)

    David Bredström

    2015-12-01

    Full Text Available This article presents a mathematical model for barge transport planning on the river Rhine, which is part of a decision support system (DSS recently taken into use by the Swiss company Omya. The system is operated by Omya’s regional office in Cologne, Germany, responsible for distribution planning at the regional distribution center (RDC in Moerdijk, the Netherlands. The distribution planning is a vital part of supply chain management of Omya’s production of Norwegian high quality calcium carbonate slurry, supplied to European paper manufacturers. The DSS operates within a vendor managed inventory (VMI setting, where the customer inventories are monitored by Omya, who decides upon the refilling days and quantities delivered by barges. The barge planning problem falls into the category of inventory routing problems (IRP and is further characterized with multiple products, heterogeneous fleet with availability restrictions (the fleet is owned by third party, vehicle compartments, dependency of barge capacity on water-level, multiple customer visits, bounded customer inventories and rolling planning horizon. There are additional modelling details which had to be considered to make it possible to employ the model in practice at a sufficient level of detail. To the best of our knowledge, we have not been able to find similar models covering all these aspects in barge planning. This article presents the developed mixed-integer programming model and discusses practical experience with its solution. Briefly, it also puts the model into the context of the entire business case of value chain optimization in Omya.

  18. Sparse Variational Analysis of Linear Mixed Models for Large Data Sets.

    Science.gov (United States)

    Armagan, Artin; Dunson, David

    2011-08-01

    It is increasingly common to be faced with longitudinal or multi-level data sets that have large numbers of predictors and/or a large sample size. Current methods of fitting and inference for mixed effects models tend to perform poorly in such settings. When there are many variables, it is appealing to allow uncertainty in subset selection and to obtain a sparse characterization of the data. Bayesian methods are available to address these goals using Markov chain Monte Carlo (MCMC), but MCMC is very computationally expensive and can be infeasible in large p and/or large n problems. As a fast approximate Bayes solution, we recommend a novel approximation to the posterior relying on variational methods. Variational methods are used to approximate the posterior of the parameters in a decomposition of the variance components, with priors chosen to obtain a sparse solution that allows selection of random effects. The method is evaluated through a simulation study, and applied to an epidemiological application.

  19. The Overlooked Potential of Generalized Linear Models in Astronomy-II: Gamma regression and photometric redshifts

    CERN Document Server

    Elliott, J; Krone-Martins, A; Cameron, E; Ishida, E E O; Hilbe, J

    2014-01-01

    Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the underlying physical processes of the data. In this article, and the companion papers of this series, we present the set of Generalized Linear Models (GLMs) as a fast alternative method for tackling general astronomical problems, including the ones related to the machine learning paradigm. To demonstrate the applicability of GLMs to inherently positive and continuous physical observables, we explore their use in estimating the photometric redshifts of galaxies from their multi-wavelength photometry. Using the gamma family with a log link function we predict redshifts from the photo-z Accuracy Testing simulated catalogue and a subset of the Sloan Digital Sky Survey from Data Release 10. We obtain fits that result in catastrophic outlier rates as low as ~1% for simulated and ~2% for...

  20. Generalized linear model for mapping discrete trait loci implemented with LASSO algorithm.

    Directory of Open Access Journals (Sweden)

    Jun Xing

    Full Text Available Generalized estimating equation (GEE algorithm under a heterogeneous residual variance model is an extension of the iteratively reweighted least squares (IRLS method for continuous traits to discrete traits. In contrast to mixture model-based expectation-maximization (EM algorithm, the GEE algorithm can well detect quantitative trait locus (QTL, especially large effect QTLs located in large marker intervals in the manner of high computing speed. Based on a single QTL model, however, the GEE algorithm has very limited statistical power to detect multiple QTLs because of ignoring other linked QTLs. In this study, the fast least absolute shrinkage and selection operator (LASSO is derived for generalized linear model (GLM with all possible link functions. Under a heterogeneous residual variance model, the LASSO for GLM is used to iteratively estimate the non-zero genetic effects of those loci over entire genome. The iteratively reweighted LASSO is therefore extended to mapping QTL for discrete traits, such as ordinal, binary, and Poisson traits. The simulated and real data analyses are conducted to demonstrate the efficiency of the proposed method to simultaneously identify multiple QTLs for binary and Poisson traits as examples.

  1. Blind Hyperspectral Unmixing Using an Extended Linear Mixing Model to Address Spectral Variability.

    Science.gov (United States)

    Drumetz, Lucas; Veganzones, Miguel-Angel; Henrot, Simon; Phlypo, Ronald; Chanussot, Jocelyn; Jutten, Christian

    2016-08-01

    Spectral unmixing is one of the main research topics in hyperspectral imaging. It can be formulated as a source separation problem, whose goal is to recover the spectral signatures of the materials present in the observed scene (called endmembers) as well as their relative proportions (called fractional abundances), and this for every pixel in the image. A linear mixture model (LMM) is often used for its simplicity and ease of use, but it implicitly assumes that a single spectrum can be completely representative of a material. However, in many scenarios, this assumption does not hold, since many factors, such as illumination conditions and intrinsic variability of the endmembers, induce modifications on the spectral signatures of the materials. In this paper, we propose an algorithm to unmix hyperspectral data using a recently proposed extended LMM. The proposed approach allows a pixelwise spatially coherent local variation of the endmembers, leading to scaled versions of reference endmembers. We also show that the classic nonnegative least squares, as well as other approaches to tackle spectral variability can be interpreted in the framework of this model. The results of the proposed algorithm on two different synthetic datasets, including one simulating the effect of topography on the measured reflectance through physical modelling, and on two real data sets, show that the proposed technique outperforms other methods aimed at addressing spectral variability, and can provide an accurate estimation of endmember variability along the scene because of the scaling factors estimation.

  2. Crystal growth and characterisation of mixed niobates for non-linear optical applications

    CERN Document Server

    Jiang, Q

    1999-01-01

    Temperature tuned NCPM has been realised by using both wavelengths. The measured phase matching temperatures increase with increasing spontaneous polarisation. KLN also has large non-linear optical coefficient (d sub 3 sub 1 =2.14 d sub 3 sub 1 sup l sup i sup N sup b sup O sup 3), a reasonably high damage threshold (1.75 times that of LiNbO sub 3), wide temperature acceptance (approx 5 deg C) and angular acceptance (approx 8 deg). Potassium sodium niobate (K sub x Na sub 1 sub - sub x NbO sub 3 , KNN) crystals have been grown and they are confirmed to be ferroelectric. However, they are unstable and break up into small pieces after a short period of time. By employing ferroelectric phenomenological theory, it is revealed that the birefringence of a ferroelectric crystal consists of two parts: one relating to a ferroelectric free of any electrical displacement and the other depending on the spontaneous polarisation. The theoretical outcomes provide a brief explanation of the experimental results in modifying ...

  3. Criteria for the Single-Valued Metric Generalized Inverses of Multi-Valued Linear Operators in Banach Spaces

    Institute of Scientific and Technical Information of China (English)

    Yu Wen WANG; Jian ZHANG; Yun An CUI

    2012-01-01

    Let X,Y be Banach spaces and M be a linear subspace in X × Y ={{x,y}|x ∈ X,y ∈ Y}.We may view M as a multi-valued linear operator from X to Y by taking M(x) ={y|{x,y} ∈ M}.In this paper,we give several criteria for a single-valued operator from Y to X to be the metric generalized inverse of the multi-valued linear operator M.The principal tool in this paper is also the generalized orthogonal decomposition theorem in Banach spaces.

  4. The Existence and Uniqueness of a New Boundary Value Problem (Type of Problem “E” for Linear System Equations of the Mixed Hyperbolic-Elliptic Type in the Multivariate Dimension with the Changing Time Direction

    Directory of Open Access Journals (Sweden)

    Mahammad A. Nurmammadov

    2015-01-01

    Full Text Available The existence and uniqueness of the boundary value problem for linear systems equations of the mixed hyperbolic-elliptic type in the multivariate domain with the changing time direction are studied. Applying methods of functional analysis, “ε-regularizing” continuation by the parameter and by means of prior estimates, the existence and uniqueness of generalized and regular solutions of a boundary problem are established in a weighted Sobolev space.

  5. Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

    Science.gov (United States)

    Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

    2016-05-01

    Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) .

  6. Simultaneous Optimality of LSE and ANOVA Estimate in General Mixed Models

    Institute of Scientific and Technical Information of China (English)

    Mi Xia WU; Song Gui WANG; Kai Fun YU

    2008-01-01

    Problems of the simultaneous optimal estimates and the optimal tests in general mixed models are considered.A necessary and sufficient condition is presented for the least squares estimate of the fixed effects and the analysis of variance (Hendreson III's) estimate of variance components being uniformly minimum variance unbiased estimates simultaneously.This result can be applied to the problems of finding uniformly optimal unbiased tests and uniformly most accurate unbiased confidential interval on parameters of interest,and for finding equivalences of several common estimates of variance components.

  7. Generalized Projective Synchronization between Two Different Neural Networks with Mixed Time Delays

    Directory of Open Access Journals (Sweden)

    Xuefei Wu

    2012-01-01

    Full Text Available The generalized projective synchronization (GPS between two different neural networks with nonlinear coupling and mixed time delays is considered. Several kinds of nonlinear feedback controllers are designed to achieve GPS between two different such neural networks. Some results for GPS of these neural networks are proved theoretically by using the Lyapunov stability theory and the LaSalle invariance principle. Moreover, by comparison, we determine an optimal nonlinear controller from several ones and provide an adaptive update law for it. Computer simulations are provided to show the effectiveness and feasibility of the proposed methods.

  8. A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds.

    Directory of Open Access Journals (Sweden)

    Ana Calabrese

    Full Text Available In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF, a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. Here, we characterize the stimulus-response function of auditory neurons using a generalized linear model (GLM. In this model, each cell's input is described by: 1 a stimulus filter (STRF; and 2 a post-spike filter, which captures dependencies on the neuron's spiking history. The output of the model is given by a series of spike trains rather than instantaneous firing rate, allowing the prediction of spike train responses to novel stimuli. We fit the model by maximum penalized likelihood to the spiking activity of zebra finch auditory midbrain neurons in response to conspecific vocalizations (songs and modulation limited (ml noise. We compare this model to normalized reverse correlation (NRC, the traditional method for STRF estimation, in terms of predictive power and the basic tuning properties of the estimated STRFs. We find that a GLM with a sparse prior predicts novel responses to both stimulus classes significantly better than NRC. Importantly, we find that STRFs from the two models derived from the same responses can differ substantially and that GLM STRFs are more consistent between stimulus classes than NRC STRFs. These results suggest that a GLM with a sparse prior provides a more accurate characterization of spectrotemporal tuning than does the NRC method when responses to complex sounds are studied in these neurons.

  9. A Mixed Integer Linear Programming Model for the Design of Remanufacturing Closed–loop Supply Chain Network

    Directory of Open Access Journals (Sweden)

    Mbarek Elbounjimi

    2015-11-01

    Full Text Available Closed-loop supply chain network design is a critical issue due to its impact on both economic and environmental performances of the supply chain. In this paper, we address the problem of designing a multi-echelon, multi-product and capacitated closed-loop supply chain network. First, a mixed-integer linear programming formulation is developed to maximize the total profit. The main contribution of the proposed model is addressing two economic viability issues of closed-loop supply chain. The first issue is the collection of sufficient quantity of end-of-life products are assured by retailers against an acquisition price. The second issue is exploiting the benefits of colocation of forward facilities and reverse facilities. The presented model is solved by LINGO for some test problems. Computational results and sensitivity analysis are conducted to show the performance of the proposed model.

  10. Non-linear mixing in coupled photonic crystal nanobeam cavities due to cross-coupling opto-mechanical mechanisms

    Energy Technology Data Exchange (ETDEWEB)

    Ramos, Daniel, E-mail: daniel.ramos@csic.es; Frank, Ian W.; Deotare, Parag B.; Bulu, Irfan; Lončar, Marko [School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138 (United States)

    2014-11-03

    We investigate the coupling between mechanical and optical modes supported by coupled, freestanding, photonic crystal nanobeam cavities. We show that localized cavity modes for a given gap between the nanobeams provide weak optomechanical coupling with out-of-plane mechanical modes. However, we show that the coupling can be significantly increased, more than an order of magnitude for the symmetric mechanical mode, due to optical resonances that arise from the interaction of the localized cavity modes with standing waves formed by the reflection from thesubstrate. Finally, amplification of motion for the symmetric mode has been observed and attributed to the strong optomechanical interaction of our hybrid system. The amplitude of these self-sustained oscillations is large enough to put the system into a non-linear oscillation regime where a mixing between the mechanical modes is experimentally observed and theoretically explained.

  11. A Green Mixed Integer Linear Programming Model for Optimization of Byproduct Gases in Iron and Steel Industry

    Institute of Scientific and Technical Information of China (English)

    Hai-ning KONG

    2015-01-01

    Byproduct gas is an important secondary energy in iron and steel industry, and its optimization is vital to cost reduction. With the development of iron and steel industry to be more eco-friendly, it is necessary to construct an integrated optimized system, taking economics, energy consumption and environment into consideration. Therefore, the environmental cost caused by pollutants discharge should be factored in total cost when optimizing byproduct gas distribution. A green mixed integer linear programming (MILP) model for the optimization of byproduct gases was established to reduce total cost, including both operation cost and environmental cost. The operation cost included penalty for gas deviation, costs of fuel and water consumption, holder booster trip penalty, and so forth; while the environmental cost consisted of penalties for both direct and indirect pollutants discharge. Case study showed that the proposed model brought an optimum solution and 2.2% of the total cost could be reduced compared with previous one.

  12. Visualizing multifactorial and multi-attribute effect sizes in linear mixed models with a view towards sensometrics

    DEFF Research Database (Denmark)

    and straightforward idea is to interpret effects relative to the residual error and to choose the proper effect size measure. For multi-attribute bar plots of F-statistics this amounts, in balanced settings, to a simple transformation of the bar heights to get them transformed into depicting what can be seen...... better comparable for factors with differences in number of levels. For mixed models, where in general the relevant error terms for the fixed effects are not the pure residual error, it is suggested to base the d-prime-like interpretation on the residual error. The methods are illustrated...... mechanisms inherently challenging effect size measure estimates in ANOVA settings....

  13. Mixed

    Directory of Open Access Journals (Sweden)

    Pau Baya

    2011-05-01

    Full Text Available Remenat (Catalan (Mixed, "revoltillo" (Scrambled in Spanish, is a dish which, in Catalunya, consists of a beaten egg cooked with vegetables or other ingredients, normally prawns or asparagus. It is delicious. Scrambled refers to the action of mixing the beaten egg with other ingredients in a pan, normally using a wooden spoon Thought is frequently an amalgam of past ideas put through a spinner and rhythmically shaken around like a cocktail until a uniform and dense paste is made. This malleable product, rather like a cake mixture can be deformed pulling it out, rolling it around, adapting its shape to the commands of one’s hands or the tool which is being used on it. In the piece Mixed, the contortion of the wood seeks to reproduce the plasticity of this slow heavy movement. Each piece lays itself on the next piece consecutively like a tongue of incandescent lava slowly advancing but with unstoppable inertia.

  14. Mixed Effects Models for Complex Data

    CERN Document Server

    Wu, Lang

    2009-01-01

    Presenting effective approaches to address missing data, measurement errors, censoring, and outliers in longitudinal data, this book covers linear, nonlinear, generalized linear, nonparametric, and semiparametric mixed effects models. It links each mixed effects model with the corresponding class of regression model for cross-sectional data and discusses computational strategies for likelihood estimations of mixed effects models. The author briefly describes generalized estimating equations methods and Bayesian mixed effects models and explains how to implement standard models using R and S-Pl

  15. The Academic Medical Center Linear Disability Score (ALDS) item bank: item response theory analysis in a mixed patient population.

    Science.gov (United States)

    Holman, Rebecca; Weisscher, Nadine; Glas, Cees A W; Dijkgraaf, Marcel G W; Vermeulen, Marinus; de Haan, Rob J; Lindeboom, Robert

    2005-12-29

    Currently, there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life. This paper examines the measurement properties of the Academic Medical Center linear disability score item bank in a mixed population. This paper uses item response theory to analyse data on 115 of 170 items from a total of 1002 respondents. These were: 551 (55%) residents of supported housing, residential care or nursing homes; 235 (23%) patients with chronic pain; 127 (13%) inpatients on a neurology ward following a stroke; and 89 (9%) patients suffering from Parkinson's disease. Of the 170 items, 115 were judged to be clinically relevant. Of these 115 items, 77 were retained in the item bank following the item response theory analysis. Of the 38 items that were excluded from the item bank, 24 had either been presented to fewer than 200 respondents or had fewer than 10% or more than 90% of responses in the category 'can carry out'. A further 11 items had different measurement properties for younger and older or for male and female respondents. Finally, 3 items were excluded because the item response theory model did not fit the data. The Academic Medical Center linear disability score item bank has promising measurement characteristics for the mixed patient population described in this paper. Further studies will be needed to examine the measurement properties of the item bank in other populations.

  16. The Academic Medical Center Linear Disability Score (ALDS) item bank: item response theory analysis in a mixed patient population

    Science.gov (United States)

    Holman, Rebecca; Weisscher, Nadine; Glas, Cees AW; Dijkgraaf, Marcel GW; Vermeulen, Marinus; de Haan, Rob J; Lindeboom, Robert

    2005-01-01

    Background Currently, there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life. This paper examines the measurement properties of the Academic Medical Center linear disability score item bank in a mixed population. Methods This paper uses item response theory to analyse data on 115 of 170 items from a total of 1002 respondents. These were: 551 (55%) residents of supported housing, residential care or nursing homes; 235 (23%) patients with chronic pain; 127 (13%) inpatients on a neurology ward following a stroke; and 89 (9%) patients suffering from Parkinson's disease. Results Of the 170 items, 115 were judged to be clinically relevant. Of these 115 items, 77 were retained in the item bank following the item response theory analysis. Of the 38 items that were excluded from the item bank, 24 had either been presented to fewer than 200 respondents or had fewer than 10% or more than 90% of responses in the category 'can carry out'. A further 11 items had different measurement properties for younger and older or for male and female respondents. Finally, 3 items were excluded because the item response theory model did not fit the data. Conclusion The Academic Medical Center linear disability score item bank has promising measurement characteristics for the mixed patient population described in this paper. Further studies will be needed to examine the measurement properties of the item bank in other populations. PMID:16381611

  17. The Academic Medical Center Linear Disability Score (ALDS item bank: item response theory analysis in a mixed patient population

    Directory of Open Access Journals (Sweden)

    Vermeulen Marinus

    2005-12-01

    Full Text Available Abstract Background Currently, there is a lot of interest in the flexible framework offered by item banks for measuring patient relevant outcomes. However, there are few item banks, which have been developed to quantify functional status, as expressed by the ability to perform activities of daily life. This paper examines the measurement properties of the Academic Medical Center linear disability score item bank in a mixed population. Methods This paper uses item response theory to analyse data on 115 of 170 items from a total of 1002 respondents. These were: 551 (55% residents of supported housing, residential care or nursing homes; 235 (23% patients with chronic pain; 127 (13% inpatients on a neurology ward following a stroke; and 89 (9% patients suffering from Parkinson's disease. Results Of the 170 items, 115 were judged to be clinically relevant. Of these 115 items, 77 were retained in the item bank following the item response theory analysis. Of the 38 items that were excluded from the item bank, 24 had either been presented to fewer than 200 respondents or had fewer than 10% or more than 90% of responses in the category 'can carry out'. A further 11 items had different measurement properties for younger and older or for male and female respondents. Finally, 3 items were excluded because the item response theory model did not fit the data. Conclusion The Academic Medical Center linear disability score item bank has promising measurement characteristics for the mixed patient population described in this paper. Further studies will be needed to examine the measurement properties of the item bank in other populations.

  18. Minimal extension of tri-bimaximal mixing and generalized Z_2 X Z_2 symmetries

    CERN Document Server

    Gupta, Shivani; Patel, Ketan M

    2011-01-01

    We discuss consequences of combining the effective $Z_2\\times Z_2$ symmetry of the tri-bimaximal neutrino mass matrix with the CP symmetry. Imposition of such generalized $Z_2\\times Z_2$ symmetries leads to predictive neutrino mass matrices determined in terms of only four parameters and leads to non-zero $\\theta_{13}$ and maximal atmospheric mixing angle and CP violating phase. It is shown that an effective generalized $Z_2\\times Z_2$ symmetry of the mass matrix can arise from the $A_4$ symmetry with specific vacuum alignment. The neutrino mass matrix in the considered model has only three real parameters and leads to determination of the absolute neutrino mass scale as a function of the reactor angle $\\theta_{13}$.

  19. MGMRES: A generalization of GMRES for solving large sparse nonsymmetric linear systems

    Energy Technology Data Exchange (ETDEWEB)

    Young, D.M.; Chen, J.Y. [Univ. of Texas, Austin, TX (United States)

    1994-12-31

    The authors are concerned with the solution of the linear system (1): Au = b, where A is a real square nonsingular matrix which is large, sparse and non-symmetric. They consider the use of Krylov subspace methods. They first choose an initial approximation u{sup (0)} to the solution {bar u} = A{sup {minus}1}B of (1). They also choose an auxiliary matrix Z which is nonsingular. For n = 1,2,{hor_ellipsis} they determine u{sup (n)} such that u{sup (n)} {minus} u{sup (0)}{epsilon}K{sub n}(r{sup (0)},A) where K{sub n}(r{sup (0)},A) is the (Krylov) subspace spanned by the Krylov vectors r{sup (0)}, Ar{sup (0)}, {hor_ellipsis}, A{sup n{minus}1}r{sup 0} and where r{sup (0)} = b{minus}Au{sup (0)}. If ZA is SPD they also require that (u{sup (n)}{minus}{bar u}, ZA(u{sup (n)}{minus}{bar u})) be minimized. If, on the other hand, ZA is not SPD, then they require that the Galerkin condition, (Zr{sup n}, v) = 0, be satisfied for all v{epsilon}K{sub n}(r{sup (0)}, A) where r{sup n} = b{minus}Au{sup (n)}. In this paper the authors consider a generalization of GMRES. This generalized method, which they refer to as `MGMRES`, is very similar to GMRES except that they let Z = A{sup T}Y where Y is a nonsingular matrix which is symmetric by not necessarily SPD.

  20. c060: Extended Inference with Lasso and Elastic-Net Regularized Cox and Generalized Linear Models

    Directory of Open Access Journals (Sweden)

    Martin Sill

    2014-12-01

    Full Text Available We have developed the R package c060 with the aim of improving R software func- tionality for high-dimensional risk prediction modeling, e.g., for prognostic modeling of survival data using high-throughput genomic data. Penalized regression models provide a statistically appealing way of building risk prediction models from high-dimensional data. The popular CRAN package glmnet implements an efficient algorithm for fitting penalized Cox and generalized linear models. However, in practical applications the data analysis will typically not stop at the point where the model has been fitted. One is for example often interested in the stability of selected features and in assessing the prediction performance of a model and we provide functions to deal with both of these tasks. Our R functions are computationally efficient and offer the possibility of speeding up computing time through parallel computing. Another feature which can drastically reduce computing time is an efficient interval-search algorithm, which we have implemented for selecting the optimal parameter combination for elastic net penalties. These functions have been useful in our daily work at the Biostatistics department (C060 of the German Cancer Research Center where prognostic modeling of patient survival data is of particular interest. Although we focus on a survival data application of penalized Cox models in this article, the functions in our R package are in general applicable to all types of regression models implemented in the glmnet package, with the exception of prediction error curves, which are specific to time-to-event data.

  1. The overlooked potential of Generalized Linear Models in astronomy-II: Gamma regression and photometric redshifts

    Science.gov (United States)

    Elliott, J.; de Souza, R. S.; Krone-Martins, A.; Cameron, E.; Ishida, E. E. O.; Hilbe, J.

    2015-04-01

    Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the underlying physical processes of the data. In this article, and the companion papers of this series, we present the set of Generalized Linear Models (GLMs) as a fast alternative method for tackling general astronomical problems, including the ones related to the machine learning paradigm. To demonstrate the applicability of GLMs to inherently positive and continuous physical observables, we explore their use in estimating the photometric redshifts of galaxies from their multi-wavelength photometry. Using the gamma family with a log link function we predict redshifts from the PHoto-z Accuracy Testing simulated catalogue and a subset of the Sloan Digital Sky Survey from Data Release 10. We obtain fits that result in catastrophic outlier rates as low as ∼1% for simulated and ∼2% for real data. Moreover, we can easily obtain such levels of precision within a matter of seconds on a normal desktop computer and with training sets that contain merely thousands of galaxies. Our software is made publicly available as a user-friendly package developed in Python, R and via an interactive web application. This software allows users to apply a set of GLMs to their own photometric catalogues and generates publication quality plots with minimum effort. By facilitating their ease of use to the astronomical community, this paper series aims to make GLMs widely known and to encourage their implementation in future large-scale projects, such as the Large Synoptic Survey Telescope.

  2. A case of mixed bullous disease of epidermolysis bullosa acquisita and linear IgA bullous dermatosis.

    Science.gov (United States)

    Osawa, Masumi; Demitsu, Toshio; Toda, Sunao; Yokokura, Hideto; Umemoto, Naoka; Yamada, Tomoko; Yoneda, Kozo; Kakurai, Maki; Yoshida, Mariko; Hashimoto, Takashi

    2005-01-01

    A 75-year-old Japanese male visited us with bullous eruptions on the extremities. Physical examination revealed large bullae on the hands, lower legs and feet. The oral mucosa was also involved. Histology disclosed subepidermal blister with inflammatory cell infiltrates in the dermis. Direct immunofluorescence showed deposits of IgG and IgA at the cutaneous basement membrane zone. Indirect immunofluorescence on 1 M NaCl-split human skin sections demonstrated that the patient's IgG antibodies reacted with the dermal side of the split, while IgA antibodies reacted with the epidermal side. Immunoblotting showed that the patient's serum reacted with the NC1 domain of type VII collagen (290-kDa epidermolysis bullosa acquisita antigen) as well as the 120-kDa linear IgA bullous dermatosis antigen, LAD-1. Systemic prednisolone resulted in a favorable response. From the clinicopathological findings, the present case is not consistent with either epidermolysis bullosa acquisita or IgA bullous dermatosis. Therefore, we regarded the case as mixed bullous disease of epidermolysis bullosa acquisita and linear IgA bullous dermatosis. Such a case has not been previously reported.

  3. Fast inference in generalized linear models via expected log-likelihoods.

    Science.gov (United States)

    Ramirez, Alexandro D; Paninski, Liam

    2014-04-01

    Generalized linear models play an essential role in a wide variety of statistical applications. This paper discusses an approximation of the likelihood in these models that can greatly facilitate computation. The basic idea is to replace a sum that appears in the exact log-likelihood by an expectation over the model covariates; the resulting "expected log-likelihood" can in many cases be computed significantly faster than the exact log-likelihood. In many neuroscience experiments the distribution over model covariates is controlled by the experimenter and the expected log-likelihood approximation becomes particularly useful; for example, estimators based on maximizing this expected log-likelihood (or a penalized version thereof) can often be obtained with orders of magnitude computational savings compared to the exact maximum likelihood estimators. A risk analysis establishes that these maximum EL estimators often come with little cost in accuracy (and in some cases even improved accuracy) compared to standard maximum likelihood estimates. Finally, we find that these methods can significantly decrease the computation time of marginal likelihood calculations for model selection and of Markov chain Monte Carlo methods for sampling from the posterior parameter distribution. We illustrate our results by applying these methods to a computationally-challenging dataset of neural spike trains obtained via large-scale multi-electrode recordings in the primate retina.

  4. Setting a generalized functional linear model (GFLM for the classification of different types of cancer

    Directory of Open Access Journals (Sweden)

    Miguel Flores

    2016-11-01

    Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

  5. Developing a methodology to predict PM10 concentrations in urban areas using generalized linear models.

    Science.gov (United States)

    Garcia, J M; Teodoro, F; Cerdeira, R; Coelho, L M R; Kumar, Prashant; Carvalho, M G

    2016-09-01

    A methodology to predict PM10 concentrations in urban outdoor environments is developed based on the generalized linear models (GLMs). The methodology is based on the relationship developed between atmospheric concentrations of air pollutants (i.e. CO, NO2, NOx, VOCs, SO2) and meteorological variables (i.e. ambient temperature, relative humidity (RH) and wind speed) for a city (Barreiro) of Portugal. The model uses air pollution and meteorological data from the Portuguese monitoring air quality station networks. The developed GLM considers PM10 concentrations as a dependent variable, and both the gaseous pollutants and meteorological variables as explanatory independent variables. A logarithmic link function was considered with a Poisson probability distribution. Particular attention was given to cases with air temperatures both below and above 25°C. The best performance for modelled results against the measured data was achieved for the model with values of air temperature above 25°C compared with the model considering all ranges of air temperatures and with the model considering only temperature below 25°C. The model was also tested with similar data from another Portuguese city, Oporto, and results found to behave similarly. It is concluded that this model and the methodology could be adopted for other cities to predict PM10 concentrations when these data are not available by measurements from air quality monitoring stations or other acquisition means.

  6. Statistical Methods for Quality Control of Steel Coils Manufacturing Process using Generalized Linear Models

    Science.gov (United States)

    García-Díaz, J. Carlos

    2009-11-01

    Fault detection and diagnosis is an important problem in process engineering. Process equipments are subject to malfunctions during operation. Galvanized steel is a value added product, furnishing effective performance by combining the corrosion resistance of zinc with the strength and formability of steel. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing and the increasingly stringent quality requirements in automotive industry has also demanded ongoing efforts in process control to make the process more robust. When faults occur, they change the relationship among these observed variables. This work compares different statistical regression models proposed in the literature for estimating the quality of galvanized steel coils on the basis of short time histories. Data for 26 batches were available. Five variables were selected for monitoring the process: the steel strip velocity, four bath temperatures and bath level. The entire data consisting of 48 galvanized steel coils was divided into sets. The first training data set was 25 conforming coils and the second data set was 23 nonconforming coils. Logistic regression is a modeling tool in which the dependent variable is categorical. In most applications, the dependent variable is binary. The results show that the logistic generalized linear models do provide good estimates of quality coils and can be useful for quality control in manufacturing process.

  7. Determination of a Differential Item Functioning Procedure Using the Hierarchical Generalized Linear Model

    Directory of Open Access Journals (Sweden)

    Tülin Acar

    2012-01-01

    Full Text Available The aim of this research is to compare the result of the differential item functioning (DIF determining with hierarchical generalized linear model (HGLM technique and the results of the DIF determining with logistic regression (LR and item response theory–likelihood ratio (IRT-LR techniques on the test items. For this reason, first in this research, it is determined whether the students encounter DIF with HGLM, LR, and IRT-LR techniques according to socioeconomic status (SES, in the Turkish, Social Sciences, and Science subtest items of the Secondary School Institutions Examination. When inspecting the correlations among the techniques in terms of determining the items having DIF, it was discovered that there was significant correlation between the results of IRT-LR and LR techniques in all subtests; merely in Science subtest, the results of the correlation between HGLM and IRT-LR techniques were found significant. DIF applications can be made on test items with other DIF analysis techniques that were not taken to the scope of this research. The analysis results, which were determined by using the DIF techniques in different sample sizes, can be compared.

  8. Linear mixed-effects models to describe length-weight relationships for yellow croaker (Larimichthys Polyactis) along the north coast of China

    Science.gov (United States)

    Jiao, Yan; Ren, Yiping

    2017-01-01

    In this study, length-weight relationships and relative condition factors were analyzed for Yellow Croaker (Larimichthys polyactis) along the north coast of China. Data covered six regions from north to south: Yellow River Estuary, Coastal Waters of Northern Shandong, Jiaozhou Bay, Coastal Waters of Qingdao, Haizhou Bay, and South Yellow Sea. In total 3,275 individuals were collected during six years (2008, 2011–2015). One generalized linear model, two simply linear models and nine linear mixed effect models that applied the effects from regions and/or years to coefficient a and/or the exponent b were studied and compared. Among these twelve models, the linear mixed effect model with random effects from both regions and years fit the data best, with lowest Akaike information criterion value and mean absolute error. In this model, the estimated a was 0.0192, with 95% confidence interval 0.0178~0.0308, and the estimated exponent b was 2.917 with 95% confidence interval 2.731~2.945. Estimates for a and b with the random effects in intercept and coefficient from Region and Year, ranged from 0.013 to 0.023 and from 2.835 to 3.017, respectively. Both regions and years had effects on parameters a and b, while the effects from years were shown to be much larger than those from regions. Except for Coastal Waters of Northern Shandong, a decreased from north to south. Condition factors relative to reference years of 1960, 1986, 2005, 2007, 2008~2009 and 2010 revealed that the body shape of Yellow Croaker became thinner in recent years. Furthermore relative condition factors varied among months, years, regions and length. The values of a and relative condition factors decreased, when the environmental pollution became worse, therefore, length-weight relationships could be an indicator for the environment quality. Results from this study provided basic description of current condition of Yellow Croaker along the north coast of China. PMID:28225777

  9. Response of the equatorial Pacific to chlorophyll pigment in a mixed layer isopycnal ocean general circulation model

    Digital Repository Service at National Institute of Oceanography (India)

    Nakamoto, S.; PrasannaKumar, S.; Oberhuber, J.M.; Ishizaka, J.; Muneyama, K.; Frouin, R.

    The influence of phytoplankton on the upper ocean dynamics and thermodynamics in the equatorial Pacific is investigated using an isopycnal ocean general circulation model (OPYC) coupled with a mixed layer model and remotely sensed chlorophyll...

  10. Assessing the tangent linear behaviour of common tracer transport schemes and their use in a linearised atmospheric general circulation model

    Directory of Open Access Journals (Sweden)

    Daniel Holdaway

    2015-09-01

    Full Text Available The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5. All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have non-linear behaviour. The piecewise parabolic method (PPM with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.

  11. Neutrino mixing matrix and masses from a generalized Friedberg-Lee model

    Science.gov (United States)

    Razzaghi, N.; Gousheh, S. S.

    2014-02-01

    The overall characteristics of the solar and atmospheric neutrino oscillation are approximately consistent with a tribimaximal form of the mixing matrix U of the lepton sector. Exact tribimaximal mixing leads to θ13=0. However, recent results from the Daya Bay and RENO experiments have established a nonzero value for θ13. Keeping the leading behavior of U as tribimaximal, we use a generalized Friedberg-Lee neutrino mass model along with a complementary ansatz to incorporate a nonzero θ13 along with CP violation. We generalize this model in two stages: In the first stage, we assume μ -τ symmetry and add imaginary components which leads to nonzero phases. In the second stage, we add a perturbation with real components which breaks the μ-τ symmetry, and this leads to a nonzero value for θ13. The combination of these two generalizations leads to CP violation. Using only two sets of the experimental data, we can fix all of the parameters of our model and predict not only values for the other experimental data, which agree well with the available data, but also the masses of neutrinos and the CP-violating phases and parameters. These predictions include the following: ⟨mνe⟩≈(0.033-0.037) eV, ⟨mνμ⟩≈(0.043-0.048) eV, ⟨mντ⟩≈(0.046-0.051) eV, and 59.21°≲δ ≲59.34°.

  12. Continuous dependence of solutions of abstract generalized linear differential equations with potential converging uniformly with a weight

    OpenAIRE

    Monteiro, G.; Tvrdý, M. (Milan)

    2014-01-01

    In this paper we continue our research on continuous dependence on a parameter of solutions to generalized linear differential equations. These equations are described by linear integral equations containing the abstract Kurzweil-Stieltjes integral. In particular, we are interested in the situation when the kernels of these equations need not have uniformly bounded variations. Our main goal is the extension of our previous results to the nonhomogeneous case. Applications to second order syste...

  13. The Relationship between Two Kinds of Generalized Convex Set-Valued Maps in Real Ordered Linear Spaces

    Directory of Open Access Journals (Sweden)

    Zhi-Ang Zhou

    2013-01-01

    Full Text Available A new notion of the ic-cone convexlike set-valued map characterized by the algebraic interior and the vector closure is introduced in real ordered linear spaces. The relationship between the ic-cone convexlike set-valued map and the nearly cone subconvexlike set-valued map is established. The results in this paper generalize some known results in the literature from locally convex spaces to linear spaces.

  14. A new iterative method for solving a system of generalized equilibrium problems, generalized mixed equilibrium problems and common fixed point problems in Hilbert spaces

    Directory of Open Access Journals (Sweden)

    Benjawan Rodjanadid

    2013-12-01

    Full Text Available In this paper, we introduce an iterative method for finding a common element of the set of solutions of a generalized mixed equilibrium problem (GMEP, the solutions of a general system of equilibrium problem and the set of common fixed points of a finite family of nonexpansive mappings in a real Hilbert space. Then, we prove that the sequence converges strongly to a common element of the above three sets. Furthermore, we apply our result to prove four new strong convergence theorems in fixed point problems, mixed equilibrium problems, generalized equilibrium problems , equilibrium problems and variational inequality.

  15. Mixed finite element - discontinuous finite volume element discretization of a general class of multicontinuum models

    Science.gov (United States)

    Ruiz-Baier, Ricardo; Lunati, Ivan

    2016-10-01

    We present a novel discretization scheme tailored to a class of multiphase models that regard the physical system as consisting of multiple interacting continua. In the framework of mixture theory, we consider a general mathematical model that entails solving a system of mass and momentum equations for both the mixture and one of the phases. The model results in a strongly coupled and nonlinear system of partial differential equations that are written in terms of phase and mixture (barycentric) velocities, phase pressure, and saturation. We construct an accurate, robust and reliable hybrid method that combines a mixed finite element discretization of the momentum equations with a primal discontinuous finite volume-element discretization of the mass (or transport) equations. The scheme is devised for unstructured meshes and relies on mixed Brezzi-Douglas-Marini approximations of phase and total velocities, on piecewise constant elements for the approximation of phase or total pressures, as well as on a primal formulation that employs discontinuous finite volume elements defined on a dual diamond mesh to approximate scalar fields of interest (such as volume fraction, total density, saturation, etc.). As the discretization scheme is derived for a general formulation of multicontinuum physical systems, it can be readily applied to a large class of simplified multiphase models; on the other, the approach can be seen as a generalization of these models that are commonly encountered in the literature and employed when the latter are not sufficiently accurate. An extensive set of numerical test cases involving two- and three-dimensional porous media are presented to demonstrate the accuracy of the method (displaying an optimal convergence rate), the physics-preserving properties of the mixed-primal scheme, as well as the robustness of the method (which is successfully used to simulate diverse physical phenomena such as density fingering, Terzaghi's consolidation

  16. Predicting stem borer density in maize using RapidEye data and generalized linear models

    Science.gov (United States)

    Abdel-Rahman, Elfatih M.; Landmann, Tobias; Kyalo, Richard; Ong'amo, George; Mwalusepo, Sizah; Sulieman, Saad; Ru, Bruno Le

    2017-05-01

    Average maize yield in eastern Africa is 2.03 t ha-1 as compared to global average of 6.06 t ha-1 due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In eastern Africa, maize yield losses due to stem borers are currently estimated between 12% and 21% of the total production. The objective of the present study was to explore the possibility of RapidEye spectral data to assess stem borer larva densities in maize fields in two study sites in Kenya. RapidEye images were acquired for the Bomet (western Kenya) test site on the 9th of December 2014 and on 27th of January 2015, and for Machakos (eastern Kenya) a RapidEye image was acquired on the 3rd of January 2015. Five RapidEye spectral bands as well as 30 spectral vegetation indices (SVIs) were utilized to predict per field maize stem borer larva densities using generalized linear models (GLMs), assuming Poisson ('Po') and negative binomial ('NB') distributions. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were used to assess the models performance using a leave-one-out cross-validation approach. The Zero-inflated NB ('ZINB') models outperformed the 'NB' models and stem borer larva densities could only be predicted during the mid growing season in December and early January in both study sites, respectively (RMSE = 0.69-1.06 and RPD = 8.25-19.57). Overall, all models performed similar when all the 30 SVIs (non-nested) and only the significant (nested) SVIs were used. The models developed could improve decision making regarding controlling maize stem borers within integrated pest management (IPM) interventions.

  17. Deriving robust and globalized robust solutions of uncertain linear programs having general convex uncertainty sets

    NARCIS (Netherlands)

    Gorissen, B.L.; Blanc, J.P.C.; den Hertog, D.; Ben-Tal, A.

    We propose a new way to derive tractable robust counterparts of a linear program based on the duality between the robust (“pessimistic”) primal problem and its “optimistic” dual. First we obtain a new convex reformulation of the dual problem of a robust linear program, and then show how to construct

  18. Increasing general practitioners' confidence and self-efficacy in managing obesity: a mixed methods study

    Science.gov (United States)

    Haesler, Emily; Elmitt, Nicholas; van Weel, Chris; Douglas, Kirsty

    2017-01-01

    Objectives Internationally, general practitioners (GPs) are being encouraged to take an active role in the care of their patients with obesity, but as yet there are few tools for them to implement within their clinics. This study assessed the self-efficacy and confidence of GPs before and after implementing a weight management programme in their practice. Design Nested mixed methods study within a 6-month feasibility trial. Setting 4 urban general practices and 1 rural general practice in Australia. Participants All vocationally registered GPs in the local region were eligible and invited to participate; 12 GPs were recruited and 11 completed the study. Interventions The Change Programme is a structured GP-delivered weight management programme that uses the therapeutic relationship between the patient and their GP to provide holistic and person-centred care. It is an evidence-based programme founded on Australian guidelines for the management of obesity in primary care. Primary outcome measures Self-efficacy and confidence of the GPs when managing obesity was measured using a quantitative survey consisting of Likert scales in conjunction with pro forma interviews. Results In line with social cognitive theory, GPs who experienced performance mastery during the pilot intervention had an increase in their confidence and self-efficacy. In particular, confidence in assisting and arranging care for patients was improved as demonstrated in the survey and supported by the qualitative data. Most importantly from the qualitative data, GPs described changing their usual practice and felt more confident to discuss obesity with all of their patients. Conclusions A structured management tool for obesity care in general practice can improve GP confidence and self-efficacy in managing obesity. Enhancing GP ‘professional self-efficacy’ is the first step to improving obesity management within general practice. Trial registration number ACTRN12614001192673; Results. PMID:28132016

  19. Assessing the Tangent Linear Behaviour of Common Tracer Transport Schemes and Their Use in a Linearised Atmospheric General Circulation Model

    Science.gov (United States)

    Holdaway, Daniel; Kent, James

    2015-01-01

    The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5). All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have nonlinear behaviour. The piecewise parabolic method (PPM) with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM) is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.

  20. Assessing the Tangent Linear Behaviour of Common Tracer Transport Schemes and Their Use in a Linearised Atmospheric General Circulation Model

    Science.gov (United States)

    Holdaway, Daniel; Kent, James

    2015-01-01

    The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5). All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have nonlinear behaviour. The piecewise parabolic method (PPM) with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM) is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.