International Nuclear Information System (INIS)
Kleijnen, J.P.C.; Helton, J.C.
1999-01-01
The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (i) Type I errors are unavoidable, (ii) Type II errors can occur when inappropriate analysis procedures are used, (iii) physical explanations should always be sought for why statistical procedures identify variables as being important, and (iv) the identification of important variables tends to be stable for independent Latin hypercube samples
International Conference on Robust Statistics
Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter
2003-01-01
Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.
Robust statistical methods with R
Jureckova, Jana
2005-01-01
Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on practical application.The authors work from underlying mathematical tools to implementation, paying special attention to the computational aspects. They cover the whole range of robust methods, including differentiable statistical functions, distance of measures, influence functions, and asymptotic distributions, in a rigorous yet approachable manner. Highlighting hands-on problem solving, many examples and computational algorithms using the R software supplement the discussion. The book examines the characteristics of robustness, estimators of real parameter, large sample properties, and goodness-of-fit tests. It...
Methodology in robust and nonparametric statistics
Jurecková, Jana; Picek, Jan
2012-01-01
Introduction and SynopsisIntroductionSynopsisPreliminariesIntroductionInference in Linear ModelsRobustness ConceptsRobust and Minimax Estimation of LocationClippings from Probability and Asymptotic TheoryProblemsRobust Estimation of Location and RegressionIntroductionM-EstimatorsL-EstimatorsR-EstimatorsMinimum Distance and Pitman EstimatorsDifferentiable Statistical FunctionsProblemsAsymptotic Representations for L-Estimators
International Conference on Robust Statistics 2015
Basu, Ayanendranath; Filzmoser, Peter; Mukherjee, Diganta
2016-01-01
This book offers a collection of recent contributions and emerging ideas in the areas of robust statistics presented at the International Conference on Robust Statistics 2015 (ICORS 2015) held in Kolkata during 12–16 January, 2015. The book explores the applicability of robust methods in other non-traditional areas which includes the use of new techniques such as skew and mixture of skew distributions, scaled Bregman divergences, and multilevel functional data methods; application areas being circular data models and prediction of mortality and life expectancy. The contributions are of both theoretical as well as applied in nature. Robust statistics is a relatively young branch of statistical sciences that is rapidly emerging as the bedrock of statistical analysis in the 21st century due to its flexible nature and wide scope. Robust statistics supports the application of parametric and other inference techniques over a broader domain than the strictly interpreted model scenarios employed in classical statis...
Robust statistics and geochemical data analysis
International Nuclear Information System (INIS)
Di, Z.
1987-01-01
Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures
Robust statistical reconstruction for charged particle tomography
Schultz, Larry Joe; Klimenko, Alexei Vasilievich; Fraser, Andrew Mcleod; Morris, Christopher; Orum, John Christopher; Borozdin, Konstantin N; Sossong, Michael James; Hengartner, Nicolas W
2013-10-08
Systems and methods for charged particle detection including statistical reconstruction of object volume scattering density profiles from charged particle tomographic data to determine the probability distribution of charged particle scattering using a statistical multiple scattering model and determine a substantially maximum likelihood estimate of object volume scattering density using expectation maximization (ML/EM) algorithm to reconstruct the object volume scattering density. The presence of and/or type of object occupying the volume of interest can be identified from the reconstructed volume scattering density profile. The charged particle tomographic data can be cosmic ray muon tomographic data from a muon tracker for scanning packages, containers, vehicles or cargo. The method can be implemented using a computer program which is executable on a computer.
Robust control charts in statistical process control
Nazir, H.Z.
2014-01-01
The presence of outliers and contaminations in the output of the process highly affects the performance of the design structures of commonly used control charts and hence makes them of less practical use. One of the solutions to deal with this problem is to use control charts which are robust
Pointwise probability reinforcements for robust statistical inference.
Frénay, Benoît; Verleysen, Michel
2014-02-01
Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. Copyright © 2013 Elsevier Ltd. All rights reserved.
Robust optimization based upon statistical theory.
Sobotta, B; Söhn, M; Alber, M
2010-08-01
distributions that are robust against interfraction and intrafraction motion alike, effectively removing the need for indiscriminate safety margins.
Highly Robust Statistical Methods in Medical Image Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf
New robust statistical procedures for the polytomous logistic regression models.
Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro
2018-05-17
This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.
Robust Control Methods for On-Line Statistical Learning
Directory of Open Access Journals (Sweden)
Capobianco Enrico
2001-01-01
Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.
Robust Combining of Disparate Classifiers Through Order Statistics
Tumer, Kagan; Ghosh, Joydeep
2001-01-01
Integrating the outputs of multiple classifiers via combiners or meta-learners has led to substantial improvements in several difficult pattern recognition problems. In this article we investigate a family of combiners based on order statistics, for robust handling of situations where there are large discrepancies in performance of individual classifiers. Based on a mathematical modeling of how the decision boundaries are affected by order statistic combiners, we derive expressions for the reductions in error expected when simple output combination methods based on the the median, the maximum and in general, the ith order statistic, are used. Furthermore, we analyze the trim and spread combiners, both based on linear combinations of the ordered classifier outputs, and show that in the presence of uneven classifier performance, they often provide substantial gains over both linear and simple order statistics combiners. Experimental results on both real world data and standard public domain data sets corroborate these findings.
Using robust statistics to improve neutron activation analysis results
International Nuclear Information System (INIS)
Zahn, Guilherme S.; Genezini, Frederico A.; Ticianelli, Regina B.; Figueiredo, Ana Maria G.
2011-01-01
Neutron activation analysis (NAA) is an analytical technique where an unknown sample is submitted to a neutron flux in a nuclear reactor, and its elemental composition is calculated by measuring the induced activity produced. By using the relative NAA method, one or more well-characterized samples (usually certified reference materials - CRMs) are irradiated together with the unknown ones, and the concentration of each element is then calculated by comparing the areas of the gamma ray peaks related to that element. When two or more CRMs are used as reference, the concentration of each element can be determined by several different ways, either using more than one gamma ray peak for that element (when available), or using the results obtained in the comparison with each CRM. Therefore, determining the best estimate for the concentration of each element in the sample can be a delicate issue. In this work, samples from three CRMs were irradiated together and the elemental concentration in one of them was calculated using the other two as reference. Two sets of peaks were analyzed for each element: a smaller set containing only the literature-recommended gamma-ray peaks and a larger one containing all peaks related to that element that could be quantified in the gamma-ray spectra; the most recommended transition was also used as a benchmark. The resulting data for each element was then reduced using up to five different statistical approaches: the usual (and not robust) unweighted and weighted means, together with three robust means: the Limitation of Relative Statistical Weight, Normalized Residuals and Rajeval. The resulting concentration values were then compared to the certified value for each element, allowing for discussion on both the performance of each statistical tool and on the best choice of peaks for each element. (author)
The power and robustness of maximum LOD score statistics.
Yoo, Y J; Mendell, N R
2008-07-01
The maximum LOD score statistic is extremely powerful for gene mapping when calculated using the correct genetic parameter value. When the mode of genetic transmission is unknown, the maximum of the LOD scores obtained using several genetic parameter values is reported. This latter statistic requires higher critical value than the maximum LOD score statistic calculated from a single genetic parameter value. In this paper, we compare the power of maximum LOD scores based on three fixed sets of genetic parameter values with the power of the LOD score obtained after maximizing over the entire range of genetic parameter values. We simulate family data under nine generating models. For generating models with non-zero phenocopy rates, LOD scores maximized over the entire range of genetic parameters yielded greater power than maximum LOD scores for fixed sets of parameter values with zero phenocopy rates. No maximum LOD score was consistently more powerful than the others for generating models with a zero phenocopy rate. The power loss of the LOD score maximized over the entire range of genetic parameters, relative to the maximum LOD score calculated using the correct genetic parameter value, appeared to be robust to the generating models.
Identifying User Profiles from Statistical Grouping Methods
Directory of Open Access Journals (Sweden)
Francisco Kelsen de Oliveira
2018-02-01
Full Text Available This research aimed to group users into subgroups according to their levels of knowledge about technology. Statistical hierarchical and non-hierarchical clustering methods were studied, compared and used in the creations of the subgroups from the similarities of the skill levels with these users’ technology. The research sample consisted of teachers who answered online questionnaires about their skills with the use of software and hardware with educational bias. The statistical methods of grouping were performed and showed the possibilities of groupings of the users. The analyses of these groups allowed to identify the common characteristics among the individuals of each subgroup. Therefore, it was possible to define two subgroups of users, one with skill in technology and another with skill with technology, so that the partial results of the research showed two main algorithms for grouping with 92% similarity in the formation of groups of users with skill with technology and the other with little skill, confirming the accuracy of the techniques of discrimination against individuals.
Robust modal curvature features for identifying multiple damage in beams
Ostachowicz, Wiesław; Xu, Wei; Bai, Runbo; Radzieński, Maciej; Cao, Maosen
2014-03-01
Curvature mode shape is an effective feature for damage detection in beams. However, it is susceptible to measurement noise, easily impairing its advantage of sensitivity to damage. To deal with this deficiency, this study formulates an improved curvature mode shape for multiple damage detection in beams based on integrating a wavelet transform (WT) and a Teager energy operator (TEO). The improved curvature mode shape, termed the WT - TEO curvature mode shape, has inherent capabilities of immunity to noise and sensitivity to damage. The proposed method is experimentally validated by identifying multiple cracks in cantilever steel beams with the mode shapes acquired using a scanning laser vibrometer. The results demonstrate that the improved curvature mode shape can identify multiple damage accurately and reliably, and it is fairly robust to measurement noise.
Automated robust generation of compact 3D statistical shape models
Vrtovec, Tomaz; Likar, Bostjan; Tomazevic, Dejan; Pernus, Franjo
2004-05-01
Ascertaining the detailed shape and spatial arrangement of anatomical structures is important not only within diagnostic settings but also in the areas of planning, simulation, intraoperative navigation, and tracking of pathology. Robust, accurate and efficient automated segmentation of anatomical structures is difficult because of their complexity and inter-patient variability. Furthermore, the position of the patient during image acquisition, the imaging device and protocol, image resolution, and other factors induce additional variations in shape and appearance. Statistical shape models (SSMs) have proven quite successful in capturing structural variability. A possible approach to obtain a 3D SSM is to extract reference voxels by precisely segmenting the structure in one, reference image. The corresponding voxels in other images are determined by registering the reference image to each other image. The SSM obtained in this way describes statistically plausible shape variations over the given population as well as variations due to imperfect registration. In this paper, we present a completely automated method that significantly reduces shape variations induced by imperfect registration, thus allowing a more accurate description of variations. At each iteration, the derived SSM is used for coarse registration, which is further improved by describing finer variations of the structure. The method was tested on 64 lumbar spinal column CT scans, from which 23, 38, 45, 46 and 42 volumes of interest containing vertebra L1, L2, L3, L4 and L5, respectively, were extracted. Separate SSMs were generated for each vertebra. The results show that the method is capable of reducing the variations induced by registration errors.
Adjustment of geochemical background by robust multivariate statistics
Zhou, D.
1985-01-01
Conventional analyses of exploration geochemical data assume that the background is a constant or slowly changing value, equivalent to a plane or a smoothly curved surface. However, it is better to regard the geochemical background as a rugged surface, varying with changes in geology and environment. This rugged surface can be estimated from observed geological, geochemical and environmental properties by using multivariate statistics. A method of background adjustment was developed and applied to groundwater and stream sediment reconnaissance data collected from the Hot Springs Quadrangle, South Dakota, as part of the National Uranium Resource Evaluation (NURE) program. Source-rock lithology appears to be a dominant factor controlling the chemical composition of groundwater or stream sediments. The most efficacious adjustment procedure is to regress uranium concentration on selected geochemical and environmental variables for each lithologic unit, and then to delineate anomalies by a common threshold set as a multiple of the standard deviation of the combined residuals. Robust versions of regression and RQ-mode principal components analysis techniques were used rather than ordinary techniques to guard against distortion caused by outliers Anomalies delineated by this background adjustment procedure correspond with uranium prospects much better than do anomalies delineated by conventional procedures. The procedure should be applicable to geochemical exploration at different scales for other metals. ?? 1985.
Second order statistics of bilinear forms of robust scatter estimators
Kammoun, Abla
2015-08-12
This paper lies in the lineage of recent works studying the asymptotic behaviour of robust-scatter estimators in the case where the number of observations and the dimension of the population covariance matrix grow at infinity with the same pace. In particular, we analyze the fluctuations of bilinear forms of the robust shrinkage estimator of covariance matrix. We show that this result can be leveraged in order to improve the design of robust detection methods. As an example, we provide an improved generalized likelihood ratio based detector which combines robustness to impulsive observations and optimality across the shrinkage parameter, the optimality being considered for the false alarm regulation.
Second order statistics of bilinear forms of robust scatter estimators
Kammoun, Abla; Couillet, Romain; Pascal, Fré dé ric
2015-01-01
. In particular, we analyze the fluctuations of bilinear forms of the robust shrinkage estimator of covariance matrix. We show that this result can be leveraged in order to improve the design of robust detection methods. As an example, we provide an improved
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
Yang, Liusha; Couillet, Romain; McKay, Matthew R.
2015-12-01
We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.
Safe Exploration for Identifying Linear Systems via Robust Optimization
Lu, Tyler; Zinkevich, Martin; Boutilier, Craig; Roy, Binz; Schuurmans, Dale
2017-01-01
Safely exploring an unknown dynamical system is critical to the deployment of reinforcement learning (RL) in physical systems where failures may have catastrophic consequences. In scenarios where one knows little about the dynamics, diverse transition data covering relevant regions of state-action space is needed to apply either model-based or model-free RL. Motivated by the cooling of Google's data centers, we study how one can safely identify the parameters of a system model with a desired ...
International Nuclear Information System (INIS)
Keitel, David; Prix, Reinhard
2015-01-01
The multi-detector F-statistic is close to optimal for detecting continuous gravitational waves (CWs) in Gaussian noise. However, it is susceptible to false alarms from instrumental artefacts, for example quasi-monochromatic disturbances (‘lines’), which resemble a CW signal more than Gaussian noise. In a recent paper (Keitel et al 2014 Phys. Rev. D 89 064023), a Bayesian model selection approach was used to derive line-robust detection statistics for CW signals, generalizing both the F-statistic and the F-statistic consistency veto technique and yielding improved performance in line-affected data. Here we investigate a generalization of the assumptions made in that paper: if a CW analysis uses data from two or more detectors with very different sensitivities, the line-robust statistics could be less effective. We investigate the boundaries within which they are still safe to use, in comparison with the F-statistic. Tests using synthetic draws show that the optimally-tuned version of the original line-robust statistic remains safe in most cases of practical interest. We also explore a simple idea on further improving the detection power and safety of these statistics, which we, however, find to be of limited practical use. (paper)
Two statistics for evaluating parameter identifiability and error reduction
Doherty, John; Hunt, Randall J.
2009-01-01
Two statistics are presented that can be used to rank input parameters utilized by a model in terms of their relative identifiability based on a given or possible future calibration dataset. Identifiability is defined here as the capability of model calibration to constrain parameters used by a model. Both statistics require that the sensitivity of each model parameter be calculated for each model output for which there are actual or presumed field measurements. Singular value decomposition (SVD) of the weighted sensitivity matrix is then undertaken to quantify the relation between the parameters and observations that, in turn, allows selection of calibration solution and null spaces spanned by unit orthogonal vectors. The first statistic presented, "parameter identifiability", is quantitatively defined as the direction cosine between a parameter and its projection onto the calibration solution space. This varies between zero and one, with zero indicating complete non-identifiability and one indicating complete identifiability. The second statistic, "relative error reduction", indicates the extent to which the calibration process reduces error in estimation of a parameter from its pre-calibration level where its value must be assigned purely on the basis of prior expert knowledge. This is more sophisticated than identifiability, in that it takes greater account of the noise associated with the calibration dataset. Like identifiability, it has a maximum value of one (which can only be achieved if there is no measurement noise). Conceptually it can fall to zero; and even below zero if a calibration problem is poorly posed. An example, based on a coupled groundwater/surface-water model, is included that demonstrates the utility of the statistics. ?? 2009 Elsevier B.V.
Robust and Reversible Audio Watermarking by Modifying Statistical Features in Time Domain
Directory of Open Access Journals (Sweden)
Shijun Xiang
2017-01-01
Full Text Available Robust and reversible watermarking is a potential technique in many sensitive applications, such as lossless audio or medical image systems. This paper presents a novel robust reversible audio watermarking method by modifying the statistic features in time domain in the way that the histogram of these statistical values is shifted for data hiding. Firstly, the original audio is divided into nonoverlapped equal-sized frames. In each frame, the use of three samples as a group generates a prediction error and a statistical feature value is calculated as the sum of all the prediction errors in the frame. The watermark bits are embedded into the frames by shifting the histogram of the statistical features. The watermark is reversible and robust to common signal processing operations. Experimental results have shown that the proposed method not only is reversible but also achieves satisfactory robustness to MP3 compression of 64 kbps and additive Gaussian noise of 35 dB.
Ganju, Jitendra; Yu, Xinxin; Ma, Guoguang Julie
2013-01-01
Formal inference in randomized clinical trials is based on controlling the type I error rate associated with a single pre-specified statistic. The deficiency of using just one method of analysis is that it depends on assumptions that may not be met. For robust inference, we propose pre-specifying multiple test statistics and relying on the minimum p-value for testing the null hypothesis of no treatment effect. The null hypothesis associated with the various test statistics is that the treatment groups are indistinguishable. The critical value for hypothesis testing comes from permutation distributions. Rejection of the null hypothesis when the smallest p-value is less than the critical value controls the type I error rate at its designated value. Even if one of the candidate test statistics has low power, the adverse effect on the power of the minimum p-value statistic is not much. Its use is illustrated with examples. We conclude that it is better to rely on the minimum p-value rather than a single statistic particularly when that single statistic is the logrank test, because of the cost and complexity of many survival trials. Copyright © 2013 John Wiley & Sons, Ltd.
Enhanced echolocation via robust statistics and super-resolution of sonar images
Kim, Kio
Echolocation is a process in which an animal uses acoustic signals to exchange information with environments. In a recent study, Neretti et al. have shown that the use of robust statistics can significantly improve the resiliency of echolocation against noise and enhance its accuracy by suppressing the development of sidelobes in the processing of an echo signal. In this research, the use of robust statistics is extended to problems in underwater explorations. The dissertation consists of two parts. Part I describes how robust statistics can enhance the identification of target objects, which in this case are cylindrical containers filled with four different liquids. Particularly, this work employs a variation of an existing robust estimator called an L-estimator, which was first suggested by Koenker and Bassett. As pointed out by Au et al.; a 'highlight interval' is an important feature, and it is closely related with many other important features that are known to be crucial for dolphin echolocation. A varied L-estimator described in this text is used to enhance the detection of highlight intervals, which eventually leads to a successful classification of echo signals. Part II extends the problem into 2 dimensions. Thanks to the advances in material and computer technology, various sonar imaging modalities are available on the market. By registering acoustic images from such video sequences, one can extract more information on the region of interest. Computer vision and image processing allowed application of robust statistics to the acoustic images produced by forward looking sonar systems, such as Dual-frequency Identification Sonar and ProViewer. The first use of robust statistics for sonar image enhancement in this text is in image registration. Random Sampling Consensus (RANSAC) is widely used for image registration. The registration algorithm using RANSAC is optimized for sonar image registration, and the performance is studied. The second use of robust
Temporal aspects of surface water quality variation using robust statistical tools.
Mustapha, Adamu; Aris, Ahmad Zaharin; Ramli, Mohammad Firuz; Juahir, Hafizan
2012-01-01
Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P < 0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P < 0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (r(p) = 0.829) and moderate (r(p) = 0.614) relationships between five-day biochemical oxygen demand (BOD(5)) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH(3)) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R(2) = 0.976 and r = 0.970, R(2) = 0.942 (P < 0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P < 0.05.
DEFF Research Database (Denmark)
2017-01-01
‘Robust – Reflections on Resilient Architecture’, is a scientific publication following the conference of the same name in November of 2017. Researches and PhD-Fellows, associated with the Masters programme: Cultural Heritage, Transformation and Restoration (Transformation), at The Royal Danish...
Robust functional statistics applied to Probability Density Function shape screening of sEMG data.
Boudaoud, S; Rix, H; Al Harrach, M; Marin, F
2014-01-01
Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.
Identifying clusters of active transportation using spatial scan statistics.
Huang, Lan; Stinchcomb, David G; Pickle, Linda W; Dill, Jennifer; Berrigan, David
2009-08-01
There is an intense interest in the possibility that neighborhood characteristics influence active transportation such as walking or biking. The purpose of this paper is to illustrate how a spatial cluster identification method can evaluate the geographic variation of active transportation and identify neighborhoods with unusually high/low levels of active transportation. Self-reported walking/biking prevalence, demographic characteristics, street connectivity variables, and neighborhood socioeconomic data were collected from respondents to the 2001 California Health Interview Survey (CHIS; N=10,688) in Los Angeles County (LAC) and San Diego County (SDC). Spatial scan statistics were used to identify clusters of high or low prevalence (with and without age-adjustment) and the quantity of time spent walking and biking. The data, a subset from the 2001 CHIS, were analyzed in 2007-2008. Geographic clusters of significantly high or low prevalence of walking and biking were detected in LAC and SDC. Structural variables such as street connectivity and shorter block lengths are consistently associated with higher levels of active transportation, but associations between active transportation and socioeconomic variables at the individual and neighborhood levels are mixed. Only one cluster with less time spent walking and biking among walkers/bikers was detected in LAC, and this was of borderline significance. Age-adjustment affects the clustering pattern of walking/biking prevalence in LAC, but not in SDC. The use of spatial scan statistics to identify significant clustering of health behaviors such as active transportation adds to the more traditional regression analysis that examines associations between behavior and environmental factors by identifying specific geographic areas with unusual levels of the behavior independent of predefined administrative units.
Robustness of S1 statistic with Hodges-Lehmann for skewed distributions
Ahad, Nor Aishah; Yahaya, Sharipah Soaad Syed; Yin, Lee Ping
2016-10-01
Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for more than two groups when the populations are normally distributed. ANOVA is highly inefficient under the influence of non- normal and heteroscedastic settings. When the assumptions are violated, researchers are looking for alternative such as Kruskal-Wallis under nonparametric or robust method. This study focused on flexible method, S1 statistic for comparing groups using median as the location estimator. S1 statistic was modified by substituting the median with Hodges-Lehmann and the default scale estimator with the variance of Hodges-Lehmann and MADn to produce two different test statistics for comparing groups. Bootstrap method was used for testing the hypotheses since the sampling distributions of these modified S1 statistics are unknown. The performance of the proposed statistic in terms of Type I error was measured and compared against the original S1 statistic, ANOVA and Kruskal-Wallis. The propose procedures show improvement compared to the original statistic especially under extremely skewed distribution.
Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations
Energy Technology Data Exchange (ETDEWEB)
Kleijnen, J.P.C.; Helton, J.C.
1999-04-01
The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are considered for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.
Identifying Statistical Dependence in Genomic Sequences via Mutual Information Estimates
Directory of Open Access Journals (Sweden)
Wojciech Szpankowski
2007-12-01
Full Text Available Questions of understanding and quantifying the representation and amount of information in organisms have become a central part of biological research, as they potentially hold the key to fundamental advances. In this paper, we demonstrate the use of information-theoretic tools for the task of identifying segments of biomolecules (DNA or RNA that are statistically correlated. We develop a precise and reliable methodology, based on the notion of mutual information, for finding and extracting statistical as well as structural dependencies. A simple threshold function is defined, and its use in quantifying the level of significance of dependencies between biological segments is explored. These tools are used in two specific applications. First, they are used for the identification of correlations between different parts of the maize zmSRp32 gene. There, we find significant dependencies between the 5Ã¢Â€Â² untranslated region in zmSRp32 and its alternatively spliced exons. This observation may indicate the presence of as-yet unknown alternative splicing mechanisms or structural scaffolds. Second, using data from the FBI's combined DNA index system (CODIS, we demonstrate that our approach is particularly well suited for the problem of discovering short tandem repeatsÃ¢Â€Â”an application of importance in genetic profiling.
Directory of Open Access Journals (Sweden)
Ling-Yun Dai
2017-01-01
Full Text Available Differential expression plays an important role in cancer diagnosis and classification. In recent years, many methods have been used to identify differentially expressed genes. However, the recognition rate and reliability of gene selection still need to be improved. In this paper, a novel constrained method named robust nonnegative matrix factorization via joint graph Laplacian and discriminative information (GLD-RNMF is proposed for identifying differentially expressed genes, in which manifold learning and the discriminative label information are incorporated into the traditional nonnegative matrix factorization model to train the objective matrix. Specifically, L2,1-norm minimization is enforced on both the error function and the regularization term which is robust to outliers and noise in gene data. Furthermore, the multiplicative update rules and the details of convergence proof are shown for the new model. The experimental results on two publicly available cancer datasets demonstrate that GLD-RNMF is an effective method for identifying differentially expressed genes.
Gene flow analysis method, the D-statistic, is robust in a wide parameter space.
Zheng, Yichen; Janke, Axel
2018-01-08
We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.
Eum, H. I.; Cannon, A. J.
2015-12-01
Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the
Mayvan, Ali D.; Aghaeinia, Hassan; Kazemi, Mohammad
2017-12-01
This paper focuses on robust transceiver design for throughput enhancement on the interference channel (IC), under imperfect channel state information (CSI). In this paper, two algorithms are proposed to improve the throughput of the multi-input multi-output (MIMO) IC. Each transmitter and receiver has, respectively, M and N antennas and IC operates in a time division duplex mode. In the first proposed algorithm, each transceiver adjusts its filter to maximize the expected value of signal-to-interference-plus-noise ratio (SINR). On the other hand, the second algorithm tries to minimize the variances of the SINRs to hedge against the variability due to CSI error. Taylor expansion is exploited to approximate the effect of CSI imperfection on mean and variance. The proposed robust algorithms utilize the reciprocity of wireless networks to optimize the estimated statistical properties in two different working modes. Monte Carlo simulations are employed to investigate sum rate performance of the proposed algorithms and the advantage of incorporating variation minimization into the transceiver design.
Gu, Jinghua; Xuan, Jianhua; Riggins, Rebecca B; Chen, Li; Wang, Yue; Clarke, Robert
2012-08-01
Identification of transcriptional regulatory networks (TRNs) is of significant importance in computational biology for cancer research, providing a critical building block to unravel disease pathways. However, existing methods for TRN identification suffer from the inclusion of excessive 'noise' in microarray data and false-positives in binding data, especially when applied to human tumor-derived cell line studies. More robust methods that can counteract the imperfection of data sources are therefore needed for reliable identification of TRNs in this context. In this article, we propose to establish a link between the quality of one target gene to represent its regulator and the uncertainty of its expression to represent other target genes. Specifically, an outlier sum statistic was used to measure the aggregated evidence for regulation events between target genes and their corresponding transcription factors. A Gibbs sampling method was then developed to estimate the marginal distribution of the outlier sum statistic, hence, to uncover underlying regulatory relationships. To evaluate the effectiveness of our proposed method, we compared its performance with that of an existing sampling-based method using both simulation data and yeast cell cycle data. The experimental results show that our method consistently outperforms the competing method in different settings of signal-to-noise ratio and network topology, indicating its robustness for biological applications. Finally, we applied our method to breast cancer cell line data and demonstrated its ability to extract biologically meaningful regulatory modules related to estrogen signaling and action in breast cancer. The Gibbs sampler MATLAB package is freely available at http://www.cbil.ece.vt.edu/software.htm. xuan@vt.edu Supplementary data are available at Bioinformatics online.
Identifying Reflectors in Seismic Images via Statistic and Syntactic Methods
Directory of Open Access Journals (Sweden)
Carlos A. Perez
2010-04-01
Full Text Available In geologic interpretation of seismic reflection data, accurate identification of reflectors is the foremost step to ensure proper subsurface structural definition. Reflector information, along with other data sets, is a key factor to predict the presence of hydrocarbons. In this work, mathematic and pattern recognition theory was adapted to design two statistical and two syntactic algorithms which constitute a tool in semiautomatic reflector identification. The interpretive power of these four schemes was evaluated in terms of prediction accuracy and computational speed. Among these, the semblance method was confirmed to render the greatest accuracy and speed. Syntactic methods offer an interesting alternative due to their inherently structural search method.
Robust global identifiability theory using potentials--Application to compartmental models.
Wongvanich, N; Hann, C E; Sirisena, H R
2015-04-01
This paper presents a global practical identifiability theory for analyzing and identifying linear and nonlinear compartmental models. The compartmental system is prolonged onto the potential jet space to formulate a set of input-output equations that are integrals in terms of the measured data, which allows for robust identification of parameters without requiring any simulation of the model differential equations. Two classes of linear and non-linear compartmental models are considered. The theory is first applied to analyze the linear nitrous oxide (N2O) uptake model. The fitting accuracy of the identified models from differential jet space and potential jet space identifiability theories is compared with a realistic noise level of 3% which is derived from sensor noise data in the literature. The potential jet space approach gave a match that was well within the coefficient of variation. The differential jet space formulation was unstable and not suitable for parameter identification. The proposed theory is then applied to a nonlinear immunological model for mastitis in cows. In addition, the model formulation is extended to include an iterative method which allows initial conditions to be accurately identified. With up to 10% noise, the potential jet space theory predicts the normalized population concentration infected with pathogens, to within 9% of the true curve. Copyright © 2015 Elsevier Inc. All rights reserved.
Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study
International Nuclear Information System (INIS)
Wu, Jia; Gensheimer, Michael F.; Dong, Xinzhe; Rubin, Daniel L.; Napel, Sandy; Diehn, Maximilian; Loo, Billy W.; Li, Ruijiang
2016-01-01
Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from "1"8F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust intratumor
Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study.
Wu, Jia; Gensheimer, Michael F; Dong, Xinzhe; Rubin, Daniel L; Napel, Sandy; Diehn, Maximilian; Loo, Billy W; Li, Ruijiang
2016-08-01
To develop an intratumor partitioning framework for identifying high-risk subregions from (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. In this institutional review board-approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). We propose a robust intratumor partitioning method to identify clinically relevant, high
Robust Intratumor Partitioning to Identify High-Risk Subregions in Lung Cancer: A Pilot Study
Energy Technology Data Exchange (ETDEWEB)
Wu, Jia; Gensheimer, Michael F.; Dong, Xinzhe [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Rubin, Daniel L. [Department of Radiology, Stanford University School of Medicine, Stanford, California (United States); Department of Medicine (Biomedical Informatics Research), Stanford University School of Medicine, Stanford, California (United States); Napel, Sandy [Department of Radiology, Stanford University School of Medicine, Stanford, California (United States); Diehn, Maximilian [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States); Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California (United States); Loo, Billy W. [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States); Li, Ruijiang, E-mail: rli2@stanford.edu [Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California (United States); Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California (United States)
2016-08-01
Purpose: To develop an intratumor partitioning framework for identifying high-risk subregions from {sup 18}F-fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) imaging and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods and Materials: In this institutional review board–approved retrospective study, we analyzed the pretreatment FDG-PET and CT scans of 44 lung cancer patients treated with radiation therapy. A novel, intratumor partitioning method was developed, based on a 2-stage clustering process: first at the patient level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor that were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI of 0.66-0.67. When restricting the analysis to patients with stage III disease (n=32), the same subregion achieved an even higher CI of 0.75 (hazard ratio 3.93, log-rank P=.002) for predicting OS, and a CI of 0.76 (hazard ratio 4.84, log-rank P=.002) for predicting OFP. In comparison, conventional imaging markers, including tumor volume, maximum standardized uptake value, and metabolic tumor volume using threshold of 50% standardized uptake value maximum, were not predictive of OS or OFP, with CI mostly below 0.60 (log-rank P>.05). Conclusion: We propose a robust
A statistical approach to identify candidate cues for nestmate recognition
DEFF Research Database (Denmark)
van Zweden, Jelle; Pontieri, Luigi; Pedersen, Jes Søe
2014-01-01
normalization, centroid,and distance calculation is most diagnostic to discriminate between NMR cues andother compounds. We find that using a “global centroid” instead of a “colony centroid”significantly improves the analysis. One reason may be that this new approach, unlikeprevious ones, provides...... than forF. exsecta, possibly due to less than ideal datasets. Nonetheless, some compound setsperformed better than others, showing that this approach can be used to identify candidatecompounds to be tested in bio-assays, and eventually crack the sophisticated code thatgoverns nestmate recognition....
Bose, S
2002-01-01
The robust statistic proposed by Creighton (Creighton J D E 1999 Phys. Rev. D 60 021101) and Allen et al (Allen et al 2001 Preprint gr-gc/010500) for the detection of stationary non-Gaussian noise is briefly reviewed. We compute the robust statistic for generic weak gravitational-wave signals in the mixture-Gaussian noise model to an accuracy higher than in those analyses, and reinterpret its role. Specifically, we obtain the coherent statistic for detecting gravitational-wave signals from inspiralling compact binaries with an arbitrary network of earth-based interferometers. Finally, we show that excess computational costs incurred owing to non-Gaussianity is negligible compared to the cost of detection in Gaussian noise.
Confronting Oahu's Water Woes: Identifying Scenarios for a Robust Evaluation of Policy Alternatives
van Rees, C. B.; Garcia, M. E.; Alarcon, T.; Sixt, G.
2013-12-01
three primary drivers of sustainability of the water supply: demand, recharge, and sea level rise. We then determined the secondary drivers shaping the primary drivers and separated them into two groups: policy-relevant drivers and external drivers. We developed a simple water balance model to calculate maximum sustainable yield based on soil properties, land cover, daily precipitation and temperature. To identify critical scenarios, the model was run over the full forecasted ranges of external drivers, such as temperature, precipitation, sea level, and population. Only the status quo of the policy drivers such as land use, water use per capita, and habitat protection has been modeled to date. However, our next steps include working with stakeholders to elicit policy strategies such as conservation regulations or zoning plans, and testing the robustness of proposed strategies with the model developed.
DEFF Research Database (Denmark)
Denwood, M.J.; McKendrick, I.J.; Matthews, L.
Introduction. There is an urgent need for a method of analysing FECRT data that is computationally simple and statistically robust. A method for evaluating the statistical power of a proposed FECRT study would also greatly enhance the current guidelines. Methods. A novel statistical framework has...... been developed that evaluates observed FECRT data against two null hypotheses: (1) the observed efficacy is consistent with the expected efficacy, and (2) the observed efficacy is inferior to the expected efficacy. The method requires only four simple summary statistics of the observed data. Power...... that the notional type 1 error rate of the new statistical test is accurate. Power calculations demonstrate a power of only 65% with a sample size of 20 treatment and control animals, which increases to 69% with 40 control animals or 79% with 40 treatment animals. Discussion. The method proposed is simple...
Ling, Zhi-Qiang; Wang, Yi; Mukaisho, Kenichi; Hattori, Takanori; Tatsuta, Takeshi; Ge, Ming-Hua; Jin, Li; Mao, Wei-Min; Sugihara, Hiroyuki
2010-06-01
Tests of differentially expressed genes (DEGs) from microarray experiments are based on the null hypothesis that genes that are irrelevant to the phenotype/stimulus are expressed equally in the target and control samples. However, this strict hypothesis is not always true, as there can be several transcriptomic background differences between target and control samples, including different cell/tissue types, different cell cycle stages and different biological donors. These differences lead to increased false positives, which have little biological/medical significance. In this article, we propose a statistical framework to identify DEGs between target and control samples from expression microarray data allowing transcriptomic background differences between these samples by introducing a modified null hypothesis that the gene expression background difference is normally distributed. We use an iterative procedure to perform robust estimation of the null hypothesis and identify DEGs as outliers. We evaluated our method using our own triplicate microarray experiment, followed by validations with reverse transcription-polymerase chain reaction (RT-PCR) and on the MicroArray Quality Control dataset. The evaluations suggest that our technique (i) results in less false positive and false negative results, as measured by the degree of agreement with RT-PCR of the same samples, (ii) can be applied to different microarray platforms and results in better reproducibility as measured by the degree of DEG identification concordance both intra- and inter-platforms and (iii) can be applied efficiently with only a few microarray replicates. Based on these evaluations, we propose that this method not only identifies more reliable and biologically/medically significant DEG, but also reduces the power-cost tradeoff problem in the microarray field. Source code and binaries freely available for download at http://comonca.org.cn/fdca/resources/softwares/deg.zip.
Saithong, Treenut; Painter, Kevin J; Millar, Andrew J
2010-12-16
A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.
Kucukgoz, Mehmet; Harmanci, Oztan; Mihcak, Mehmet K.; Venkatesan, Ramarathnam
2005-03-01
In this paper, we propose a novel semi-blind video watermarking scheme, where we use pseudo-random robust semi-global features of video in the three dimensional wavelet transform domain. We design the watermark sequence via solving an optimization problem, such that the features of the mark-embedded video are the quantized versions of the features of the original video. The exact realizations of the algorithmic parameters are chosen pseudo-randomly via a secure pseudo-random number generator, whose seed is the secret key, that is known (resp. unknown) by the embedder and the receiver (resp. by the public). We experimentally show the robustness of our algorithm against several attacks, such as conventional signal processing modifications and adversarial estimation attacks.
A robust statistical method for association-based eQTL analysis.
Directory of Open Access Journals (Sweden)
Ning Jiang
Full Text Available It has been well established that theoretical kernel for recently surging genome-wide association study (GWAS is statistical inference of linkage disequilibrium (LD between a tested genetic marker and a putative locus affecting a disease trait. However, LD analysis is vulnerable to several confounding factors of which population stratification is the most prominent. Whilst many methods have been proposed to correct for the influence either through predicting the structure parameters or correcting inflation in the test statistic due to the stratification, these may not be feasible or may impose further statistical problems in practical implementation.We propose here a novel statistical method to control spurious LD in GWAS from population structure by incorporating a control marker into testing for significance of genetic association of a polymorphic marker with phenotypic variation of a complex trait. The method avoids the need of structure prediction which may be infeasible or inadequate in practice and accounts properly for a varying effect of population stratification on different regions of the genome under study. Utility and statistical properties of the new method were tested through an intensive computer simulation study and an association-based genome-wide mapping of expression quantitative trait loci in genetically divergent human populations.The analyses show that the new method confers an improved statistical power for detecting genuine genetic association in subpopulations and an effective control of spurious associations stemmed from population structure when compared with other two popularly implemented methods in the literature of GWAS.
Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P
2015-03-01
Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.
DEFF Research Database (Denmark)
Madsen, Tobias
2017-01-01
In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...
An optimization methodology for identifying robust process integration investments under uncertainty
International Nuclear Information System (INIS)
Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith; Patriksson, Michael
2009-01-01
Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)
An optimization methodology for identifying robust process integration investments under uncertainty
Energy Technology Data Exchange (ETDEWEB)
Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden); Patriksson, Michael [Department of Mathematical Sciences, Chalmers University of Technology and Department of Mathematical Sciences, University of Gothenburg, SE-412 96 Goeteborg (Sweden)
2009-02-15
Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures. (author)
Multivariate meta-analysis: a robust approach based on the theory of U-statistic.
Ma, Yan; Mazumdar, Madhu
2011-10-30
Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Allen, Bruce; Creighton, Jolien D.E.; Flanagan, Eanna E.; Romano, Joseph D.
2003-01-01
In a previous paper (paper I), we derived a set of near-optimal signal detection techniques for gravitational wave detectors whose noise probability distributions contain non-Gaussian tails. The methods modify standard methods by truncating or clipping sample values which lie in those non-Gaussian tails. The methods were derived, in the frequentist framework, by minimizing false alarm probabilities at fixed false detection probability in the limit of weak signals. For stochastic signals, the resulting statistic consisted of a sum of an autocorrelation term and a cross-correlation term; it was necessary to discard 'by hand' the autocorrelation term in order to arrive at the correct, generalized cross-correlation statistic. In the present paper, we present an alternative derivation of the same signal detection techniques from within the Bayesian framework. We compute, for both deterministic and stochastic signals, the probability that a signal is present in the data, in the limit where the signal-to-noise ratio squared per frequency bin is small, where the signal is nevertheless strong enough to be detected (integrated signal-to-noise ratio large compared to 1), and where the total probability in the non-Gaussian tail part of the noise distribution is small. We show that, for each model considered, the resulting probability is to a good approximation a monotonic function of the detection statistic derived in paper I. Moreover, for stochastic signals, the new Bayesian derivation automatically eliminates the problematic autocorrelation term
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.
2007-02-01
Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.
Wang, Hao; Wang, Qunwei; He, Ming
2018-05-01
In order to investigate and improve the level of detection technology of water content in liquid chemical reagents of domestic laboratories, proficiency testing provider PT0031 (CNAS) has organized proficiency testing program of water content in toluene, 48 laboratories from 18 provinces/cities/municipals took part in the PT. This paper introduces the implementation process of proficiency testing for determination of water content in toluene, including sample preparation, homogeneity and stability test, the results of statistics of iteration robust statistic technique and analysis, summarized and analyzed those of the different test standards which are widely used in the laboratories, put forward the technological suggestions for the improvement of the test quality of water content. Satisfactory results were obtained by 43 laboratories, amounting to 89.6% of the total participating laboratories.
Robust optimization of the output voltage of nanogenerators by statistical design of experiments
Song, Jinhui; Xie, Huizhi; Wu, Wenzhuo; Roshan Joseph, V.; Jeff Wu, C. F.; Wang, Zhong Lin
2010-01-01
Nanogenerators were first demonstrated by deflecting aligned ZnO nanowires using a conductive atomic force microscopy (AFM) tip. The output of a nanogenerator is affected by three parameters: tip normal force, tip scanning speed, and tip abrasion. In this work, systematic experimental studies have been carried out to examine the combined effects of these three parameters on the output, using statistical design of experiments. A statistical model has been built to analyze the data and predict the optimal parameter settings. For an AFM tip of cone angle 70° coated with Pt, and ZnO nanowires with a diameter of 50 nm and lengths of 600 nm to 1 μm, the optimized parameters for the nanogenerator were found to be a normal force of 137 nN and scanning speed of 40 μm/s, rather than the conventional settings of 120 nN for the normal force and 30 μm/s for the scanning speed. A nanogenerator with the optimized settings has three times the average output voltage of one with the conventional settings. © 2010 Tsinghua University Press and Springer-Verlag Berlin Heidelberg.
From statistical proofs of the Kochen-Specker theorem to noise-robust noncontextuality inequalities
Kunjwal, Ravi; Spekkens, Robert W.
2018-05-01
The Kochen-Specker theorem rules out models of quantum theory wherein projective measurements are assigned outcomes deterministically and independently of context. This notion of noncontextuality is not applicable to experimental measurements because these are never free of noise and thus never truly projective. For nonprojective measurements, therefore, one must drop the requirement that an outcome be assigned deterministically in the model and merely require that it be assigned a distribution over outcomes in a manner that is context-independent. By demanding context independence in the representation of preparations as well, one obtains a generalized principle of noncontextuality that also supports a quantum no-go theorem. Several recent works have shown how to derive inequalities on experimental data which, if violated, demonstrate the impossibility of finding a generalized-noncontextual model of this data. That is, these inequalities do not presume quantum theory and, in particular, they make sense without requiring an operational analog of the quantum notion of projectiveness. We here describe a technique for deriving such inequalities starting from arbitrary proofs of the Kochen-Specker theorem. It extends significantly previous techniques that worked only for logical proofs, which are based on sets of projective measurements that fail to admit of any deterministic noncontextual assignment, to the case of statistical proofs, which are based on sets of projective measurements that d o admit of some deterministic noncontextual assignments, but not enough to explain the quantum statistics.
Robust optimization of the output voltage of nanogenerators by statistical design of experiments
Song, Jinhui
2010-09-01
Nanogenerators were first demonstrated by deflecting aligned ZnO nanowires using a conductive atomic force microscopy (AFM) tip. The output of a nanogenerator is affected by three parameters: tip normal force, tip scanning speed, and tip abrasion. In this work, systematic experimental studies have been carried out to examine the combined effects of these three parameters on the output, using statistical design of experiments. A statistical model has been built to analyze the data and predict the optimal parameter settings. For an AFM tip of cone angle 70° coated with Pt, and ZnO nanowires with a diameter of 50 nm and lengths of 600 nm to 1 μm, the optimized parameters for the nanogenerator were found to be a normal force of 137 nN and scanning speed of 40 μm/s, rather than the conventional settings of 120 nN for the normal force and 30 μm/s for the scanning speed. A nanogenerator with the optimized settings has three times the average output voltage of one with the conventional settings. © 2010 Tsinghua University Press and Springer-Verlag Berlin Heidelberg.
International Nuclear Information System (INIS)
Janczura, Joanna; Trück, Stefan; Weron, Rafał; Wolff, Rodney C.
2013-01-01
An important issue in fitting stochastic models to electricity spot prices is the estimation of a component to deal with trends and seasonality in the data. Unfortunately, estimation routines for the long-term and short-term seasonal pattern are usually quite sensitive to extreme observations, known as electricity price spikes. Improved robustness of the model can be achieved by (a) filtering the data with some reasonable procedure for outlier detection, and then (b) using estimation and testing procedures on the filtered data. In this paper we examine the effects of different treatments of extreme observations on model estimation and on determining the number of spikes (outliers). In particular we compare results for the estimation of the seasonal and stochastic components of electricity spot prices using either the original or filtered data. We find significant evidence for a superior estimation of both the seasonal short-term and long-term components when the data have been treated carefully for outliers. Overall, our findings point out the substantial impact the treatment of extreme observations may have on these issues and, therefore, also on the pricing of electricity derivatives like futures and option contracts. An added value of our study is the ranking of different filtering techniques used in the energy economics literature, suggesting which methods could be and which should not be used for spike identification. - Highlights: • First comprehensive study on the impact of spikes on seasonal pattern estimation • The effects of different treatments of spikes on model estimation are examined. • Cleaning spot prices for outliers yields superior estimates of the seasonal pattern. • Removing outliers provides better parameter estimates for the stochastic process. • Rankings of filtering techniques suggested in the literature are provided
A hybrid finite element - statistical energy analysis approach to robust sound transmission modeling
Reynders, Edwin; Langley, Robin S.; Dijckmans, Arne; Vermeir, Gerrit
2014-09-01
When considering the sound transmission through a wall in between two rooms, in an important part of the audio frequency range, the local response of the rooms is highly sensitive to uncertainty in spatial variations in geometry, material properties and boundary conditions, which have a wave scattering effect, while the local response of the wall is rather insensitive to such uncertainty. For this mid-frequency range, a computationally efficient modeling strategy is adopted that accounts for this uncertainty. The partitioning wall is modeled deterministically, e.g. with finite elements. The rooms are modeled in a very efficient, nonparametric stochastic way, as in statistical energy analysis. All components are coupled by means of a rigorous power balance. This hybrid strategy is extended so that the mean and variance of the sound transmission loss can be computed as well as the transition frequency that loosely marks the boundary between low- and high-frequency behavior of a vibro-acoustic component. The method is first validated in a simulation study, and then applied for predicting the airborne sound insulation of a series of partition walls of increasing complexity: a thin plastic plate, a wall consisting of gypsum blocks, a thicker masonry wall and a double glazing. It is found that the uncertainty caused by random scattering is important except at very high frequencies, where the modal overlap of the rooms is very high. The results are compared with laboratory measurements, and both are found to agree within the prediction uncertainty in the considered frequency range.
Robust classification of motor imagery EEG signals using statistical time–domain features
International Nuclear Information System (INIS)
Khorshidtalab, A; Salami, M J E; Hamedi, M
2013-01-01
The tradeoff between computational complexity and speed, in addition to growing demands for real-time BMI (brain–machine interface) systems, expose the necessity of applying methods with least possible complexity. Willison amplitude (WAMP) and slope sign change (SSC) are two promising time–domain features only if the right threshold value is defined for them. To overcome the drawback of going through trial and error for the determination of a suitable threshold value, modified WAMP and modified SSC are proposed in this paper. Besides, a comprehensive assessment of statistical time–domain features in which their effectiveness is evaluated with a support vector machine (SVM) is presented. To ensure the accuracy of the results obtained by the SVM, the performance of each feature is reassessed with supervised fuzzy C-means. The general assessment shows that every subject had at least one of his performances near or greater than 80%. The obtained results prove that for BMI applications, in which a few errors can be tolerated, these combinations of feature–classifier are suitable. Moreover, features that could perform satisfactorily were selected for feature combination. Combinations of the selected features are evaluated with the SVM, and they could significantly improve the results, in some cases, up to full accuracy. (paper)
Directory of Open Access Journals (Sweden)
Gray John C
2006-11-01
Full Text Available Abstract Background The floral dip method of transformation by immersion of inflorescences in a suspension of Agrobacterium is the method of choice for Arabidopsis transformation. The presence of a marker, usually antibiotic- or herbicide-resistance, allows identification of transformed seedlings from untransformed seedlings. Seedling selection is a lengthy process which does not always lead to easily identifiable transformants. Selection for kanamycin-, phosphinothricin- and hygromycin B-resistance commonly takes 7–10 d and high seedling density and fungal contamination may result in failure to recover transformants. Results A method for identifying transformed seedlings in as little as 3.25 d has been developed. Arabidopsis T1 seeds obtained after floral dip transformation are plated on 1% agar containing MS medium and kanamycin, phosphinothricin or hygromycin B, as appropriate. After a 2-d stratification period, seeds are subjected to a regime of 4–6 h light, 48 h dark and 24 h light (3.25 d. Kanamycin-resistant and phosphinothricin-resistant seedlings are easily distinguished from non-resistant seedlings by green expanded cotyledons whereas non-resistant seedlings have pale unexpanded cotyledons. Seedlings grown on hygromycin B differ from those grown on kanamycin and phosphinothricin as both resistant and non-resistant seedlings are green. However, hygromycin B-resistant seedlings are easily identified as they have long hypocotyls (0.8–1.0 cm whereas non-resistant seedlings have short hypocotyls (0.2–0.4 cm. Conclusion The method presented here is an improvement on current selection methods as it allows quicker identification of transformed seedlings: transformed seedlings are easily discernable from non-transformants in as little as 3.25 d in comparison to the 7–10 d required for selection using current protocols.
Kim, Seongho; Li, Lang
2014-02-01
The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Pimperl, Alexander F; Rodriguez, Hector P; Schmittdiel, Julie A; Shortell, Stephen M
2018-06-01
To identify positive deviant (PD) physician organizations of Accountable Care Organizations (ACOs) with robust performance management systems (PMSYS). Third National Survey of Physician Organizations (NSPO3, n = 1,398). Organizational and external factors from NSPO3 were analyzed. Linear regression estimated the association of internal and contextual factors on PMSYS. Two cutpoints (75th/90th percentiles) identified PDs with the largest residuals and highest PMSYS scores. A total of 65 and 41 PDs were identified using 75th and 90th percentiles cutpoints, respectively. The 90th percentile more strongly differentiated PDs from non-PDs. Having a high proportion of vulnerable patients appears to constrain PMSYS development. Our PD identification method increases the likelihood that PD organizations selected for in-depth inquiry are high-performing organizations that exceed expectations. © Health Research and Educational Trust.
Purba, H.; Musu, J. T.; Diria, S. A.; Permono, W.; Sadjati, O.; Sopandi, I.; Ruzi, F.
2018-03-01
Well logging data provide many geological information and its trends resemble nonlinear or non-stationary signals. As long well log data recorded, there will be external factors can interfere or influence its signal resolution. A sensitive signal analysis is required to improve the accuracy of logging interpretation which it becomes an important thing to determine sequence stratigraphy. Complete Ensemble Empirical Mode Decomposition (CEEMD) is one of nonlinear and non-stationary signal analysis method which decomposes complex signal into a series of intrinsic mode function (IMF). Gamma Ray and Spontaneous Potential well log parameters decomposed into IMF-1 up to IMF-10 and each of its combination and correlation makes physical meaning identification. It identifies the stratigraphy and cycle sequence and provides an effective signal treatment method for sequence interface. This method was applied to BRK- 30 and BRK-13 well logging data. The result shows that the combination of IMF-5, IMF-6, and IMF-7 pattern represent short-term and middle-term while IMF-9 and IMF-10 represent the long-term sedimentation which describe distal front and delta front facies, and inter-distributary mouth bar facies, respectively. Thus, CEEMD clearly can determine the different sedimentary layer interface and better identification of the cycle of stratigraphic base level.
Robust Statistical Face Frontalization
Sagonas, Christos; Panagakis, Yannis; Zafeiriou, Stefanos; Pantic, Maja
2015-01-01
Recently, it has been shown that excellent results can be achieved in both facial landmark localization and pose-invariant face recognition. These breakthroughs are attributed to the efforts of the community to manually annotate facial images in many different poses and to collect 3D facial data. In
Directory of Open Access Journals (Sweden)
Li He
2014-01-01
Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.
International Nuclear Information System (INIS)
Svensson, Elin; Berntsson, Thore; Stroemberg, Ann-Brith
2009-01-01
This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO 2 emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO 2 emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives
Energy Technology Data Exchange (ETDEWEB)
Svensson, Elin [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden)], E-mail: elin.svensson@chalmers.se; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)
2009-03-15
This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, (doi:10.1016/j.enpol.2008.10.023)] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives.
Energy Technology Data Exchange (ETDEWEB)
Svensson, Elin; Berntsson, Thore [Department of Energy and Environment, Division of Heat and Power Technology, Chalmers University of Technology, SE-412 96 Goeteborg (Sweden); Stroemberg, Ann-Brith [Fraunhofer-Chalmers Research Centre for Industrial Mathematics, Chalmers Science Park, SE-412 88 Gothenburg (Sweden)
2009-03-15
This paper presents a case study on the optimization of process integration investments in a pulp mill considering uncertainties in future electricity and biofuel prices and CO{sub 2} emissions charges. The work follows the methodology described in Svensson et al. [Svensson, E., Berntsson, T., Stroemberg, A.-B., Patriksson, M., 2008b. An optimization methodology for identifying robust process integration investments under uncertainty. Energy Policy, in press, doi:10.1016/j.enpol.2008.10.023] where a scenario-based approach is proposed for the modelling of uncertainties. The results show that the proposed methodology provides a way to handle the time dependence and the uncertainties of the parameters. For the analyzed case, a robust solution is found which turns out to be a combination of two opposing investment strategies. The difference between short-term and strategic views for the investment decision is analyzed and it is found that uncertainties are increasingly important to account for as a more strategic view is employed. Furthermore, the results imply that the obvious effect of policy instruments aimed at decreasing CO{sub 2} emissions is, in applications like this, an increased profitability for all energy efficiency investments, and not as much a shift between different alternatives. (author)
International Nuclear Information System (INIS)
Keitel, David
2016-01-01
Non-axisymmetries in rotating neutron stars emit quasi-monochromatic gravitational waves. These long-duration ‘continuous wave’ signals are among the main search targets of ground-based interferometric detectors. However, standard detection methods are susceptible to false alarms from instrumental artefacts that resemble a continuous-wave signal. Past work [Keitel, Prix, Papa, Leaci and Siddiqi 2014, Phys. Rev. D 89 064023] showed that a Bayesian approach, based on an explicit model of persistent single-detector disturbances, improves robustness against such artefacts. Since many strong outliers in semi-coherent searches of LIGO data are caused by transient disturbances that last only a few hours or days, I describe in a recent paper [Keitel D 2015, LIGO-P1500159] how to extend this approach to cover transient disturbances, and demonstrate increased sensitivity in realistic simulated data. Additionally, neutron stars could emit transient signals which, for a limited time, also follow the continuous-wave signal model. As a pragmatic alternative to specialized transient searches, I demonstrate how to make standard semi-coherent continuous-wave searches more sensitive to transient signals. Focusing on the time-scale of a single segment in the semi-coherent search, Bayesian model selection yields a simple detection statistic without a significant increase in computational cost. This proceedings contribution gives a brief overview of both works. (paper)
Directory of Open Access Journals (Sweden)
Turnbull Arran K
2012-08-01
Full Text Available Abstract Background Affymetrix GeneChips and Illumina BeadArrays are the most widely used commercial single channel gene expression microarrays. Public data repositories are an extremely valuable resource, providing array-derived gene expression measurements from many thousands of experiments. Unfortunately many of these studies are underpowered and it is desirable to improve power by combining data from more than one study; we sought to determine whether platform-specific bias precludes direct integration of probe intensity signals for combined reanalysis. Results Using Affymetrix and Illumina data from the microarray quality control project, from our own clinical samples, and from additional publicly available datasets we evaluated several approaches to directly integrate intensity level expression data from the two platforms. After mapping probe sequences to Ensembl genes we demonstrate that, ComBat and cross platform normalisation (XPN, significantly outperform mean-centering and distance-weighted discrimination (DWD in terms of minimising inter-platform variance. In particular we observed that DWD, a popular method used in a number of previous studies, removed systematic bias at the expense of genuine biological variability, potentially reducing legitimate biological differences from integrated datasets. Conclusion Normalised and batch-corrected intensity-level data from Affymetrix and Illumina microarrays can be directly combined to generate biologically meaningful results with improved statistical power for robust, integrated reanalysis.
Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.
2015-03-01
During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.
A comparison of statistical methods for identifying out-of-date systematic reviews.
Directory of Open Access Journals (Sweden)
Porjai Pattanittum
Full Text Available BACKGROUND: Systematic reviews (SRs can provide accurate and reliable evidence, typically about the effectiveness of health interventions. Evidence is dynamic, and if SRs are out-of-date this information may not be useful; it may even be harmful. This study aimed to compare five statistical methods to identify out-of-date SRs. METHODS: A retrospective cohort of SRs registered in the Cochrane Pregnancy and Childbirth Group (CPCG, published between 2008 and 2010, were considered for inclusion. For each eligible CPCG review, data were extracted and "3-years previous" meta-analyses were assessed for the need to update, given the data from the most recent 3 years. Each of the five statistical methods was used, with random effects analyses throughout the study. RESULTS: Eighty reviews were included in this study; most were in the area of induction of labour. The numbers of reviews identified as being out-of-date using the Ottawa, recursive cumulative meta-analysis (CMA, and Barrowman methods were 34, 7, and 7 respectively. No reviews were identified as being out-of-date using the simulation-based power method, or the CMA for sufficiency and stability method. The overall agreement among the three discriminating statistical methods was slight (Kappa = 0.14; 95% CI 0.05 to 0.23. The recursive cumulative meta-analysis, Ottawa, and Barrowman methods were practical according to the study criteria. CONCLUSION: Our study shows that three practical statistical methods could be applied to examine the need to update SRs.
DEFF Research Database (Denmark)
Sangüesa, Adrià Arbués; Moeslund, Thomas B.; Bahnsen, Chris Holmberg
2017-01-01
Advanced statistics have proved to be a crucial tool for basketball coaches in order to improve training skills. Indeed, the performance of the team can be further optimized by studying the behaviour of players under certain conditions. In the United States of America, companies such as STATS...... or Second Spectrum use a complex multi-camera setup to deliver advanced statistics to all NBA teams, but the price of this service is far beyond the budget of the vast majority of European teams. For this reason, a first prototype based on positioning sensors is presented. An experimental dataset has been...... created and meaningful basketball features have been extracted. 97.9% accuracy is obtained using Support Vector Machines when identifying 5 different classic plays: floppy offense, pick and roll, press break, post-up situation and fast breaks. After recognizing these plays in video sequences, advanced...
Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B
2013-03-23
Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.
Ing, Alex; Schwarzbauer, Christian
2014-01-01
Functional connectivity has become an increasingly important area of research in recent years. At a typical spatial resolution, approximately 300 million connections link each voxel in the brain with every other. This pattern of connectivity is known as the functional connectome. Connectivity is often compared between experimental groups and conditions. Standard methods used to control the type 1 error rate are likely to be insensitive when comparisons are carried out across the whole connectome, due to the huge number of statistical tests involved. To address this problem, two new cluster based methods--the cluster size statistic (CSS) and cluster mass statistic (CMS)--are introduced to control the family wise error rate across all connectivity values. These methods operate within a statistical framework similar to the cluster based methods used in conventional task based fMRI. Both methods are data driven, permutation based and require minimal statistical assumptions. Here, the performance of each procedure is evaluated in a receiver operator characteristic (ROC) analysis, utilising a simulated dataset. The relative sensitivity of each method is also tested on real data: BOLD (blood oxygen level dependent) fMRI scans were carried out on twelve subjects under normal conditions and during the hypercapnic state (induced through the inhalation of 6% CO2 in 21% O2 and 73%N2). Both CSS and CMS detected significant changes in connectivity between normal and hypercapnic states. A family wise error correction carried out at the individual connection level exhibited no significant changes in connectivity.
Smith, R.; Kasprzyk, J. R.; Balaji, R.
2017-12-01
In light of deeply uncertain factors like future climate change and population shifts, responsible resource management will require new types of information and strategies. For water utilities, this entails potential expansion and efficient management of water supply infrastructure systems for changes in overall supply; changes in frequency and severity of climate extremes such as droughts and floods; and variable demands, all while accounting for conflicting long and short term performance objectives. Multiobjective Evolutionary Algorithms (MOEAs) are emerging decision support tools that have been used by researchers and, more recently, water utilities to efficiently generate and evaluate thousands of planning portfolios. The tradeoffs between conflicting objectives are explored in an automated way to produce (often large) suites of portfolios that strike different balances of performance. Once generated, the sets of optimized portfolios are used to support relatively subjective assertions of priorities and human reasoning, leading to adoption of a plan. These large tradeoff sets contain information about complex relationships between decisions and between groups of decisions and performance that, until now, has not been quantitatively described. We present a novel use of Multivariate Regression Trees (MRTs) to analyze tradeoff sets to reveal these relationships and critical decisions. Additionally, when MRTs are applied to tradeoff sets developed for different realizations of an uncertain future, they can identify decisions that are robust across a wide range of conditions and produce fundamental insights about the system being optimized.
Van Wynsberge, Simon; Gilbert, Antoine; Guillemot, Nicolas; Heintz, Tom; Tremblay-Boyer, Laura
2017-07-01
Extensive biological field surveys are costly and time consuming. To optimize sampling and ensure regular monitoring on the long term, identifying informative indicators of anthropogenic disturbances is a priority. In this study, we used 1800 candidate indicators by combining metrics measured from coral, fish, and macro-invertebrate assemblages surveyed from 2006 to 2012 in the vicinity of an ongoing mining project in the Voh-Koné-Pouembout lagoon, New Caledonia. We performed a power analysis to identify a subset of indicators which would best discriminate temporal changes due to a simulated chronic anthropogenic impact. Only 4% of tested indicators were likely to detect a 10% annual decrease of values with sufficient power (>0.80). Corals generally exerted higher statistical power than macro-invertebrates and fishes because of lower natural variability and higher occurrence. For the same reasons, higher taxonomic ranks provided higher power than lower taxonomic ranks. Nevertheless, a number of families of common sedentary or sessile macro-invertebrates and fishes also performed well in detecting changes: Echinometridae, Isognomidae, Muricidae, Tridacninae, Arcidae, and Turbinidae for macro-invertebrates and Pomacentridae, Labridae, and Chaetodontidae for fishes. Interestingly, these families did not provide high power in all geomorphological strata, suggesting that the ability of indicators in detecting anthropogenic impacts was closely linked to reef geomorphology. This study provides a first operational step toward identifying statistically relevant indicators of anthropogenic disturbances in New Caledonia's coral reefs, which can be useful in similar tropical reef ecosystems where little information is available regarding the responses of ecological indicators to anthropogenic disturbances.
Sadatsafavi, Mohsen; Xie, Hui; Etminan, Mahyar; Johnson, Kate; FitzGerald, J Mark
2018-01-01
There is minimal evidence on the extent to which the occurrence of a severe acute exacerbation of COPD that results in hospitalization affects the subsequent disease course. Previous studies on this topic did not generate causally-interpretable estimates. Our aim was to use corrected methodology to update previously reported estimates of the associations between previous and future exacerbations in these patients. Using administrative health data in British Columbia, Canada (1997-2012), we constructed a cohort of patients with at least one severe exacerbation, defined as an episode of inpatient care with the main diagnosis of COPD based on international classification of diseases (ICD) codes. We applied a random-effects 'joint frailty' survival model that is particularly developed for the analysis of recurrent events in the presence of competing risk of death and heterogeneity among individuals in their rate of events. Previous severe exacerbations entered the model as dummy-coded time-dependent covariates, and the model was adjusted for several observable patient and disease characteristics. 35,994 individuals (mean age at baseline 73.7, 49.8% female, average follow-up 3.21 years) contributed 34,271 severe exacerbations during follow-up. The first event was associated with a hazard ratio (HR) of 1.75 (95%CI 1.69-1.82) for the risk of future severe exacerbations. This risk decreased to HR = 1.36 (95%CI 1.30-1.42) for the second event and to 1.18 (95%CI 1.12-1.25) for the third event. The first two severe exacerbations that occurred during follow-up were also significantly associated with increased risk of all-cause mortality. There was substantial heterogeneity in the individual-specific rate of severe exacerbations. Even after adjusting for observable characteristics, individuals in the 97.5th percentile of exacerbation rate had 5.6 times higher rate of severe exacerbations than those in the 2.5th percentile. Using robust statistical methodology that controlled
Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior
2011-09-23
Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.
Directory of Open Access Journals (Sweden)
Zhai Chengxiang
2010-05-01
Full Text Available Abstract Background Large-scale genomic studies often identify large gene lists, for example, the genes sharing the same expression patterns. The interpretation of these gene lists is generally achieved by extracting concepts overrepresented in the gene lists. This analysis often depends on manual annotation of genes based on controlled vocabularies, in particular, Gene Ontology (GO. However, the annotation of genes is a labor-intensive process; and the vocabularies are generally incomplete, leaving some important biological domains inadequately covered. Results We propose a statistical method that uses the primary literature, i.e. free-text, as the source to perform overrepresentation analysis. The method is based on a statistical framework of mixture model and addresses the methodological flaws in several existing programs. We implemented this method within a literature mining system, BeeSpace, taking advantage of its analysis environment and added features that facilitate the interactive analysis of gene sets. Through experimentation with several datasets, we showed that our program can effectively summarize the important conceptual themes of large gene sets, even when traditional GO-based analysis does not yield informative results. Conclusions We conclude that the current work will provide biologists with a tool that effectively complements the existing ones for overrepresentation analysis from genomic experiments. Our program, Genelist Analyzer, is freely available at: http://workerbee.igb.uiuc.edu:8080/BeeSpace/Search.jsp
Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.
2018-02-01
In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.
Use of multivariate statistics to identify unreliable data obtained using CASA.
Martínez, Luis Becerril; Crispín, Rubén Huerta; Mendoza, Maximino Méndez; Gallegos, Oswaldo Hernández; Martínez, Andrés Aragón
2013-06-01
In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.
Directory of Open Access Journals (Sweden)
Yi-Ju Chen
Full Text Available S-glutathionylation, the covalent attachment of a glutathione (GSH to the sulfur atom of cysteine, is a selective and reversible protein post-translational modification (PTM that regulates protein activity, localization, and stability. Despite its implication in the regulation of protein functions and cell signaling, the substrate specificity of cysteine S-glutathionylation remains unknown. Based on a total of 1783 experimentally identified S-glutathionylation sites from mouse macrophages, this work presents an informatics investigation on S-glutathionylation sites including structural factors such as the flanking amino acids composition and the accessible surface area (ASA. TwoSampleLogo presents that positively charged amino acids flanking the S-glutathionylated cysteine may influence the formation of S-glutathionylation in closed three-dimensional environment. A statistical method is further applied to iteratively detect the conserved substrate motifs with statistical significance. Support vector machine (SVM is then applied to generate predictive model considering the substrate motifs. According to five-fold cross-validation, the SVMs trained with substrate motifs could achieve an enhanced sensitivity, specificity, and accuracy, and provides a promising performance in an independent test set. The effectiveness of the proposed method is demonstrated by the correct identification of previously reported S-glutathionylation sites of mouse thioredoxin (TXN and human protein tyrosine phosphatase 1b (PTP1B. Finally, the constructed models are adopted to implement an effective web-based tool, named GSHSite (http://csb.cse.yzu.edu.tw/GSHSite/, for identifying uncharacterized GSH substrate sites on the protein sequences.
Novel Application of Statistical Methods to Identify New Urinary Incontinence Risk Factors
Directory of Open Access Journals (Sweden)
Theophilus O. Ogunyemi
2012-01-01
Full Text Available Longitudinal data for studying urinary incontinence (UI risk factors are rare. Data from one study, the hallmark Medical, Epidemiological, and Social Aspects of Aging (MESA, have been analyzed in the past; however, repeated measures analyses that are crucial for analyzing longitudinal data have not been applied. We tested a novel application of statistical methods to identify UI risk factors in older women. MESA data were collected at baseline and yearly from a sample of 1955 men and women in the community. Only women responding to the 762 baseline and 559 follow-up questions at one year in each respective survey were examined. To test their utility in mining large data sets, and as a preliminary step to creating a predictive index for developing UI, logistic regression, generalized estimating equations (GEEs, and proportional hazard regression (PHREG methods were used on the existing MESA data. The GEE and PHREG combination identified 15 significant risk factors associated with developing UI out of which six of them, namely, urinary frequency, urgency, any urine loss, urine loss after emptying, subject’s anticipation, and doctor’s proactivity, are found most highly significant by both methods. These six factors are potential candidates for constructing a future UI predictive index.
A method to identify dependencies between organizational factors using statistical independence test
International Nuclear Information System (INIS)
Kim, Y.; Chung, C.H.; Kim, C.; Jae, M.; Jung, J.H.
2004-01-01
A considerable number of studies on organizational factors in nuclear power plants have been made especially in recent years, most of which have assumed organizational factors to be independent. However, since organizational factors characterize the organization in terms of safety and efficiency etc. and there would be some factors that have close relations between them. Therefore, from whatever point of view, if we want to identify the characteristics of an organization, the dependence relationships should be considered to get an accurate result. In this study the organization of a reference nuclear power plant in Korea was analyzed for the trip cases of that plant using 20 organizational factors that Jacobs and Haber had suggested: 1) coordination of work, 2) formalization, 3) organizational knowledge, 4) roles and responsibilities, 5) external communication, 6) inter-department communications, 7) intra-departmental communications, 8) organizational culture, 9) ownership, 10) safety culture, 11) time urgency, 12) centralization, 13) goal prioritization, 14) organizational learning, 15) problem identification, 16) resource allocation, 17) performance evaluation, 18) personnel selection, 19) technical knowledge, and 20) training. By utilizing the results of the analysis, a method to identify the dependence relationships between organizational factors is presented. The statistical independence test for the analysis result of the trip cases is adopted to reveal dependencies. This method is geared to the needs to utilize many kinds of data that has been obtained as the operating years of nuclear power plants increase, and more reliable dependence relations may be obtained by using these abundant data
Directory of Open Access Journals (Sweden)
G. Lointier
2008-02-01
Full Text Available Identifying and tracking the projection of magnetospheric regions on the high-latitude ionosphere is of primary importance for studying the Solar Wind-Magnetosphere-Ionosphere system and for space weather applications. By its unique spatial coverage and temporal resolution, the Super Dual Auroral Radar Network (SuperDARN provides key parameters, such as the Doppler spectral width, which allows the monitoring of the ionospheric footprint of some magnetospheric boundaries in near real-time. In this study, we present the first results of a statistical approach for monitoring these magnetospheric boundaries. The singular value decomposition is used as a data reduction tool to describe the backscattered echoes with a small set of parameters. One of these is strongly correlated with the Doppler spectral width, and can thus be used as a proxy for it. Based on this, we propose a Bayesian classifier for identifying the spectral width boundary, which is classically associated with the Polar Cap boundary. The results are in good agreement with previous studies. Two advantages of the method are: the possibility to apply it in near real-time, and its capacity to select the appropriate threshold level for the boundary detection.
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Identify fracture-critical regions inside the proximal femur using statistical parametric mapping
Li, Wenjun; Kornak, John; Harris, Tamara; Keyak, Joyce; Li, Caixia; Lu, Ying; Cheng, Xiaoguang; Lang, Thomas
2009-01-01
We identified regions inside the proximal femur that are most strongly associated with hip fracture. Bone densitometry based on such fracture-critical regions showed improved power in discriminating fracture patients from controls. Introduction Hip fractures typically occur in lateral falls, with focal mechanical failure of the sub-volumes of tissue in which the applied stress exceeds the strength. In this study, we describe a new methodology to identify proximal femoral tissue elements with highest association with hip fracture. We hypothesize that bone mineral density (BMD) measured in such sub-volumes discriminates hip fracture risk better than BMD in standard anatomic regions such as the femoral neck and trochanter. Materials and Methods We employed inter-subject registration to transform hip QCT images of 37 patients with hip fractures and 38 age-matched controls into a voxel-based statistical atlas. Within voxels, we performed t-tests between the two groups to identify the regions which differed most. We then randomly divided the 75 scans into a training set and a test set. From the training set, we derived a fracture-driven region of interest (ROI) based on association with fracture. In the test set, we measured BMD in this ROI to determine fracture discrimination efficacy using ROC analysis. Additionally, we compared the BMD distribution differences between the 29 patients with neck fractures and the 8 patients with trochanteric fractures. Results By evaluating fracture discrimination power based on ROC analysis, the fracture-driven ROI had an AUC (area under curve) of 0.92, while anatomic ROIs (including the entire proximal femur, the femoral neck, trochanter and their cortical and trabecular compartments) had AUC values between 0.78 and 0.87. We also observed that the neck fracture patients had lower BMD (p=0.014) in a small region near the femoral neck and the femoral head, and patients with trochanteric fractures had lower BMD in trochanteric regions
Statistical Evaluation of the Identified Structural Parameters of an idling Offshore Wind Turbine
International Nuclear Information System (INIS)
Kramers, Hendrik C.; Van der Valk, Paul L.C.; Van Wingerden, Jan-Willem
2016-01-01
With the increased need for renewable energy, new offshore wind farms are being developed at an unprecedented scale. However, as the costs of offshore wind energy are still too high, design optimization and new innovations are required for lowering its cost. The design of modern day offshore wind turbines relies on numerical models for estimating ultimate and fatigue loads of the turbines. The dynamic behavior and the resulting structural loading of the turbines is determined for a large part by its structural properties, such as the natural frequencies and damping ratios. Hence, it is important to obtain accurate estimates of these modal properties. For this purpose stochastic subspace identification (SSI), in combination with clustering and statistical evaluation methods, is used to obtain the variance of the identified modal properties of an installed 3.6MW offshore wind turbine in idling conditions. It is found that one is able to obtain confidence intervals for the means of eigenfrequencies and damping ratios of the fore-aft and side-side modes of the wind turbine. (paper)
Directory of Open Access Journals (Sweden)
Mark Frogley
2013-01-01
Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.
Nimptsch, Ulrike; Wengler, Annelene; Mansky, Thomas
2016-11-01
In Germany, nationwide hospital discharge data (DRG statistics provided by the research data centers of the Federal Statistical Office and the Statistical Offices of the 'Länder') are increasingly used as data source for health services research. Within this data hospitals can be separated via their hospital identifier ([Institutionskennzeichen] IK). However, this hospital identifier primarily designates the invoicing unit and is not necessarily equivalent to one hospital location. Aiming to investigate direction and extent of possible bias in hospital-level analyses this study examines the continuity of the hospital identifier within a cross-sectional and longitudinal approach and compares the results to official hospital census statistics. Within the DRG statistics from 2005 to 2013 the annual number of hospitals as classified by hospital identifiers was counted for each year of observation. The annual number of hospitals derived from DRG statistics was compared to the number of hospitals in the official census statistics 'Grunddaten der Krankenhäuser'. Subsequently, the temporal continuity of hospital identifiers in the DRG statistics was analyzed within cohorts of hospitals. Until 2013, the annual number of hospital identifiers in the DRG statistics fell by 175 (from 1,725 to 1,550). This decline affected only providers with small or medium case volume. The number of hospitals identified in the DRG statistics was lower than the number given in the census statistics (e.g., in 2013 1,550 IK vs. 1,668 hospitals in the census statistics). The longitudinal analyses revealed that the majority of hospital identifiers persisted in the years of observation, while one fifth of hospital identifiers changed. In cross-sectional studies of German hospital discharge data the separation of hospitals via the hospital identifier might lead to underestimating the number of hospitals and consequential overestimation of caseload per hospital. Discontinuities of hospital
Jaffee, Sara R.; Strait, Luciana B.; Odgers, Candice L.
2011-01-01
Longitudinal, epidemiological studies have identified robust risk factors for youth antisocial behavior, including harsh and coercive discipline, maltreatment, smoking during pregnancy, divorce, teen parenthood, peer deviance, parental psychopathology, and social disadvantage. Nevertheless, because this literature is largely based on observational studies, it remains unclear whether these risk factors have truly causal effects. Identifying causal risk factors for antisocial behavior would be informative for intervention efforts and for studies that test whether individuals are differentially susceptible to risk exposures. In this paper, we identify the challenges to causal inference posed by observational studies and describe quasi-experimental methods and statistical innovations that may move us beyond discussions of risk factors to allow for stronger causal inference. We then review studies that use these methods and we evaluate whether robust risk factors identified from observational studies are likely to play a causal role in the emergence and development of youth antisocial behavior. For most of the risk factors we review, there is evidence that they have causal effects. However, these effects are typically smaller than those reported in observational studies, suggesting that familial confounding, social selection, and misidentification might also explain some of the association between risk exposures and antisocial behavior. For some risk factors (e.g., smoking during pregnancy, parent alcohol problems) the evidence is weak that they have environmentally mediated effects on youth antisocial behavior. We discuss the implications of these findings for intervention efforts to reduce antisocial behavior and for basic research on the etiology and course of antisocial behavior. PMID:22023141
Zhang, Mingjing; Wen, Ming; Zhang, Zhi-Min; Lu, Hongmei; Liang, Yizeng; Zhan, Dejian
2015-03-01
Retention time shift is one of the most challenging problems during the preprocessing of massive chromatographic datasets. Here, an improved version of the moving window fast Fourier transform cross-correlation algorithm is presented to perform nonlinear and robust alignment of chromatograms by analyzing the shifts matrix generated by moving window procedure. The shifts matrix in retention time can be estimated by fast Fourier transform cross-correlation with a moving window procedure. The refined shift of each scan point can be obtained by calculating the mode of corresponding column of the shifts matrix. This version is simple, but more effective and robust than the previously published moving window fast Fourier transform cross-correlation method. It can handle nonlinear retention time shift robustly if proper window size has been selected. The window size is the only one parameter needed to adjust and optimize. The properties of the proposed method are investigated by comparison with the previous moving window fast Fourier transform cross-correlation and recursive alignment by fast Fourier transform using chromatographic datasets. The pattern recognition results of a gas chromatography mass spectrometry dataset of metabolic syndrome can be improved significantly after preprocessing by this method. Furthermore, the proposed method is available as an open source package at https://github.com/zmzhang/MWFFT2. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T
2015-01-01
MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.
International Nuclear Information System (INIS)
2005-01-01
For the years 2004 and 2005 the figures shown in the tables of Energy Review are partly preliminary. The annual statistics published in Energy Review are presented in more detail in a publication called Energy Statistics that comes out yearly. Energy Statistics also includes historical time-series over a longer period of time (see e.g. Energy Statistics, Statistics Finland, Helsinki 2004.) The applied energy units and conversion coefficients are shown in the back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes, precautionary stock fees and oil pollution fees
Jäger, Jörg M; Schöllhorn, Wolfgang I
2012-04-01
Offensive and defensive systems of play represent important aspects of team sports. They include the players' positions at certain situations during a match, i.e., when players have to be on specific positions on the court. Patterns of play emerge based on the formations of the players on the court. Recognition of these patterns is important to react adequately and to adjust own strategies to the opponent. Furthermore, the ability to apply variable patterns of play seems to be promising since they make it harder for the opponent to adjust. The purpose of this study is to identify different team tactical patterns in volleyball and to analyze differences in variability. Overall 120 standard situations of six national teams in women's volleyball are analyzed during a world championship tournament. Twenty situations from each national team are chosen, including the base defence position (start configuration) and the two players block with middle back deep (end configuration). The shapes of the defence formations at the start and end configurations during the defence of each national team as well as the variability of these defence formations are statistically analyzed. Furthermore these shapes data are used to train multilayer perceptrons in order to test whether artificial neural networks can recognize the teams by their tactical patterns. Results show significant differences between the national teams in both the base defence position at the start and the two players block with middle back deep at the end of the standard defence situation. Furthermore, the national teams show significant differences in variability of the defence systems and start-positions are more variable than the end-positions. Multilayer perceptrons are able to recognize the teams at an average of 98.5%. It is concluded that defence systems in team sports are highly individual at a competitive level and variable even in standard situations. Artificial neural networks can be used to recognize
International Nuclear Information System (INIS)
2001-01-01
For the year 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions from the use of fossil fuels, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in 2000, Energy exports by recipient country in 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
1999-01-01
For the year 1998 and the year 1999, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g. Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 1999, Energy exports by recipient country in January-June 1999, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
International Nuclear Information System (INIS)
2003-01-01
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
2004-01-01
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO 2 -emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees
International Nuclear Information System (INIS)
2000-01-01
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy also includes historical time series over a longer period (see e.g., Energiatilastot 1999, Statistics Finland, Helsinki 2000, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO 2 -emissions, Electricity supply, Energy imports by country of origin in January-June 2000, Energy exports by recipient country in January-June 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Derkach, Andriy; Chiang, Theodore; Gong, Jiafen; Addis, Laura; Dobbins, Sara; Tomlinson, Ian; Houlston, Richard; Pal, Deb K; Strug, Lisa J
2014-08-01
Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. lisa.strug@utoronto.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Hill, Mary C.
2010-01-01
Doherty and Hunt (2009) present important ideas for first-order-second moment sensitivity analysis, but five issues are discussed in this comment. First, considering the composite-scaled sensitivity (CSS) jointly with parameter correlation coefficients (PCC) in a CSS/PCC analysis addresses the difficulties with CSS mentioned in the introduction. Second, their new parameter identifiability statistic actually is likely to do a poor job of parameter identifiability in common situations. The statistic instead performs the very useful role of showing how model parameters are included in the estimated singular value decomposition (SVD) parameters. Its close relation to CSS is shown. Third, the idea from p. 125 that a suitable truncation point for SVD parameters can be identified using the prediction variance is challenged using results from Moore and Doherty (2005). Fourth, the relative error reduction statistic of Doherty and Hunt is shown to belong to an emerging set of statistics here named perturbed calculated variance statistics. Finally, the perturbed calculated variance statistics OPR and PPR mentioned on p. 121 are shown to explicitly include the parameter null-space component of uncertainty. Indeed, OPR and PPR results that account for null-space uncertainty have appeared in the literature since 2000.
Molina-Perez, Edmundo
It is widely recognized that international environmental technological change is key to reduce the rapidly rising greenhouse gas emissions of emerging nations. In 2010, the United Nations Framework Convention on Climate Change (UNFCCC) Conference of the Parties (COP) agreed to the creation of the Green Climate Fund (GCF). This new multilateral organization has been created with the collective contributions of COP members, and has been tasked with directing over USD 100 billion per year towards investments that can enhance the development and diffusion of clean energy technologies in both advanced and emerging nations (Helm and Pichler, 2015). The landmark agreement arrived at the COP 21 has reaffirmed the key role that the GCF plays in enabling climate mitigation as it is now necessary to align large scale climate financing efforts with the long-term goals agreed at Paris 2015. This study argues that because of the incomplete understanding of the mechanics of international technological change, the multiplicity of policy options and ultimately the presence of climate and technological change deep uncertainty, climate financing institutions such as the GCF, require new analytical methods for designing long-term robust investment plans. Motivated by these challenges, this dissertation shows that the application of new analytical methods, such as Robust Decision Making (RDM) and Exploratory Modeling (Lempert, Popper and Bankes, 2003) to the study of international technological change and climate policy provides useful insights that can be used for designing a robust architecture of international technological cooperation for climate change mitigation. For this study I developed an exploratory dynamic integrated assessment model (EDIAM) which is used as the scenario generator in a large computational experiment. The scope of the experimental design considers an ample set of climate and technological scenarios. These scenarios combine five sources of uncertainty
Directory of Open Access Journals (Sweden)
Hae-Hiang Song
2012-06-01
Full Text Available Large-scale copy number variants (CNVs in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional FST measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the FST estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific FST and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.
Taheri, Shaghayegh; Fevens, Thomas; Bui, Tien D.
2017-02-01
Computerized assessments for diagnosis or malignancy grading of cyto-histopathological specimens have drawn increased attention in the field of digital pathology. Automatic segmentation of cell nuclei is a fundamental step in such automated systems. Despite considerable research, nuclei segmentation is still a challenging task due noise, nonuniform illumination, and most importantly, in 2D projection images, overlapping and touching nuclei. In most published approaches, nuclei refinement is a post-processing step after segmentation, which usually refers to the task of detaching the aggregated nuclei or merging the over-segmented nuclei. In this work, we present a novel segmentation technique which effectively addresses the problem of individually segmenting touching or overlapping cell nuclei during the segmentation process. The proposed framework is a region-based segmentation method, which consists of three major modules: i) the image is passed through a color deconvolution step to extract the desired stains; ii) then the generalized fast radial symmetry transform is applied to the image followed by non-maxima suppression to specify the initial seed points for nuclei, and their corresponding GFRS ellipses which are interpreted as the initial nuclei borders for segmentation; iii) finally, these nuclei border initial curves are evolved through the use of a statistical level-set approach along with topology preserving criteria for segmentation and separation of nuclei at the same time. The proposed method is evaluated using Hematoxylin and Eosin, and fluorescent stained images, performing qualitative and quantitative analysis, showing that the method outperforms thresholding and watershed segmentation approaches.
Hill, Stephen E.; Schvaneveldt, Shane J.
2011-01-01
This article presents an educational exercise in which statistical process control charts are constructed and used to identify the Steroids Era in American professional baseball. During this period (roughly 1993 until the present), numerous baseball players were alleged or proven to have used banned, performance-enhancing drugs. Also observed…
Directory of Open Access Journals (Sweden)
Rauch Ł.
2015-09-01
Full Text Available The coupled finite element multiscale simulations (FE2 require costly numerical procedures in both macro and micro scales. Attempts to improve numerical efficiency are focused mainly on two areas of development, i.e. parallelization/distribution of numerical procedures and simplification of virtual material representation. One of the representatives of both mentioned areas is the idea of Statistically Similar Representative Volume Element (SSRVE. It aims at the reduction of the number of finite elements in micro scale as well as at parallelization of the calculations in micro scale which can be performed without barriers. The simplification of computational domain is realized by transformation of sophisticated images of material microstructure into artificially created simple objects being characterized by similar features as their original equivalents. In existing solutions for two-phase steels SSRVE is created on the basis of the analysis of shape coefficients of hard phase in real microstructure and searching for a representative simple structure with similar shape coefficients. Optimization techniques were used to solve this task. In the present paper local strains and stresses are added to the cost function in optimization. Various forms of the objective function composed of different elements were investigated and used in the optimization procedure for the creation of the final SSRVE. The results are compared as far as the efficiency of the procedure and uniqueness of the solution are considered. The best objective function composed of shape coefficients, as well as of strains and stresses, was proposed. Examples of SSRVEs determined for the investigated two-phase steel using that objective function are demonstrated in the paper. Each step of SSRVE creation is investigated from computational efficiency point of view. The proposition of implementation of the whole computational procedure on modern High Performance Computing (HPC
To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis
Directory of Open Access Journals (Sweden)
Yiqing Guan
2013-01-01
Full Text Available Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents.
Kawata, Masaaki; Sato, Chikara
2007-06-01
In determining the three-dimensional (3D) structure of macromolecular assemblies in single particle analysis, a large representative dataset of two-dimensional (2D) average images from huge number of raw images is a key for high resolution. Because alignments prior to averaging are computationally intensive, currently available multireference alignment (MRA) software does not survey every possible alignment. This leads to misaligned images, creating blurred averages and reducing the quality of the final 3D reconstruction. We present a new method, in which multireference alignment is harmonized with classification (multireference multiple alignment: MRMA). This method enables a statistical comparison of multiple alignment peaks, reflecting the similarities between each raw image and a set of reference images. Among the selected alignment candidates for each raw image, misaligned images are statistically excluded, based on the principle that aligned raw images of similar projections have a dense distribution around the correctly aligned coordinates in image space. This newly developed method was examined for accuracy and speed using model image sets with various signal-to-noise ratios, and with electron microscope images of the Transient Receptor Potential C3 and the sodium channel. In every data set, the newly developed method outperformed conventional methods in robustness against noise and in speed, creating 2D average images of higher quality. This statistically harmonized alignment-classification combination should greatly improve the quality of single particle analysis.
Azcorra, A; Chiroque, L F; Cuevas, R; Fernández Anta, A; Laniado, H; Lillo, R E; Romo, J; Sguera, C
2018-05-03
Billions of users interact intensively every day via Online Social Networks (OSNs) such as Facebook, Twitter, or Google+. This makes OSNs an invaluable source of information, and channel of actuation, for sectors like advertising, marketing, or politics. To get the most of OSNs, analysts need to identify influential users that can be leveraged for promoting products, distributing messages, or improving the image of companies. In this report we propose a new unsupervised method, Massive Unsupervised Outlier Detection (MUOD), based on outliers detection, for providing support in the identification of influential users. MUOD is scalable, and can hence be used in large OSNs. Moreover, it labels the outliers as of shape, magnitude, or amplitude, depending of their features. This allows classifying the outlier users in multiple different classes, which are likely to include different types of influential users. Applying MUOD to a subset of roughly 400 million Google+ users, it has allowed identifying and discriminating automatically sets of outlier users, which present features associated to different definitions of influential users, like capacity to attract engagement, capacity to attract a large number of followers, or high infection capacity.
International Nuclear Information System (INIS)
Kleijnen, J.P.C.; Helton, J.C.
1999-01-01
Procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses are described and illustrated. These procedures attempt to detect increasingly complex patterns in scatterplots and involve the identification of (i) linear relationships with correlation coefficients, (ii) monotonic relationships with rank correlation coefficients, (iii) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (iv) trends in variability as defined by variances and interquartile ranges, and (v) deviations from randomness as defined by the chi-square statistic. A sequence of example analyses with a large model for two-phase fluid flow illustrates how the individual procedures can differ in the variables that they identify as having effects on particular model outcomes. The example analyses indicate that the use of a sequence of procedures is a good analysis strategy and provides some assurance that an important effect is not overlooked
Kwon, O.; Kim, W.; Kim, J.
2017-12-01
Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics
Reese, Sarah E; Archer, Kellie J; Therneau, Terry M; Atkinson, Elizabeth J; Vachon, Celine M; de Andrade, Mariza; Kocher, Jean-Pierre A; Eckel-Passow, Jeanette E
2013-11-15
Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal component analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. We present an extension of PCA to quantify the existence of batch effects, called guided PCA (gPCA). We describe a test statistic that uses gPCA to test whether a batch effect exists. We apply our proposed test statistic derived using gPCA to simulated data and to two copy number variation case studies: the first study consisted of 614 samples from a breast cancer family study using Illumina Human 660 bead-chip arrays, whereas the second case study consisted of 703 samples from a family blood pressure study that used Affymetrix SNP Array 6.0. We demonstrate that our statistic has good statistical properties and is able to identify significant batch effects in two copy number variation case studies. We developed a new statistic that uses gPCA to identify whether batch effects exist in high-throughput genomic data. Although our examples pertain to copy number data, gPCA is general and can be used on other data types as well. The gPCA R package (Available via CRAN) provides functionality and data to perform the methods in this article. reesese@vcu.edu
THE GROWTH POINTS OF STATISTICAL METHODS
Orlov A. I.
2014-01-01
On the basis of a new paradigm of applied mathematical statistics, data analysis and economic-mathematical methods are identified; we have also discussed five topical areas in which modern applied statistics is developing as well as the other statistical methods, i.e. five "growth points" – nonparametric statistics, robustness, computer-statistical methods, statistics of interval data, statistics of non-numeric data
Energy Technology Data Exchange (ETDEWEB)
Wu, J; Gensheimer, M; Dong, X; Rubin, D; Napel, S; Diehn, M; Loo, B; Li, R [Stanford University, Palo Alto, CA (United States)
2016-06-15
Purpose: To develop an intra-tumor partitioning framework for identifying high-risk subregions from 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) and CT imaging, and to test whether tumor burden associated with the high-risk subregions is prognostic of outcomes in lung cancer. Methods: In this institutional review board-approved retrospective study, we analyzed the pre-treatment FDG-PET and CT scans of 44 lung cancer patients treated with radiotherapy. A novel, intra-tumor partitioning method was developed based on a two-stage clustering process: first at patient-level, each tumor was over-segmented into many superpixels by k-means clustering of integrated PET and CT images; next, tumor subregions were identified by merging previously defined superpixels via population-level hierarchical clustering. The volume associated with each of the subregions was evaluated using Kaplan-Meier analysis regarding its prognostic capability in predicting overall survival (OS) and out-of-field progression (OFP). Results: Three spatially distinct subregions were identified within each tumor, which were highly robust to uncertainty in PET/CT co-registration. Among these, the volume of the most metabolically active and metabolically heterogeneous solid component of the tumor was predictive of OS and OFP on the entire cohort, with a concordance index or CI = 0.66–0.67. When restricting the analysis to patients with stage III disease (n = 32), the same subregion achieved an even higher CI = 0.75 (HR = 3.93, logrank p = 0.002) for predicting OS, and a CI = 0.76 (HR = 4.84, logrank p = 0.002) for predicting OFP. In comparison, conventional imaging markers including tumor volume, SUVmax and MTV50 were not predictive of OS or OFP, with CI mostly below 0.60 (p < 0.001). Conclusion: We propose a robust intra-tumor partitioning method to identify clinically relevant, high-risk subregions in lung cancer. We envision that this approach will be applicable to identifying useful
Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne
2017-01-01
Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study
Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin
2014-01-01
Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874
Bosomprah, Samuel; Dotse-Gborgbortsi, Winfred; Aboagye, Patrick; Matthews, Zoe
2016-11-01
To identify and evaluate clusters of births that occurred outside health facilities in Ghana for targeted intervention. A retrospective study was conducted using a convenience sample of live births registered in Ghanaian health facilities from January 1 to December 31, 2014. Data were extracted from the district health information system. A spatial scan statistic was used to investigate clusters of home births through a discrete Poisson probability model. Scanning with a circular spatial window was conducted only for clusters with high rates of such deliveries. The district was used as the geographic unit of analysis. The likelihood P value was estimated using Monte Carlo simulations. Ten statistically significant clusters with a high rate of home birth were identified. The relative risks ranged from 1.43 ("least likely" cluster; P=0.001) to 1.95 ("most likely" cluster; P=0.001). The relative risks of the top five "most likely" clusters ranged from 1.68 to 1.95; these clusters were located in Ashanti, Brong Ahafo, and the Western, Eastern, and Greater regions of Accra. Health facility records, geospatial techniques, and geographic information systems provided locally relevant information to assist policy makers in delivering targeted interventions to small geographic areas. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.
J Olive, David
2017-01-01
This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given. The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory. The robust techniques are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis. A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...
Lukas, J M; Hawkins, D M; Kinsel, M L; Reneau, J K
2005-11-01
The objective of this study was to examine the relationship between monthly Dairy Herd Improvement (DHI) subclinical mastitis and new infection rate estimates and daily bulk tank somatic cell count (SCC) summarized by statistical process control tools. Dairy Herd Improvement Association test-day subclinical mastitis and new infection rate estimates along with daily or every other day bulk tank SCC data were collected for 12 mo of 2003 from 275 Upper Midwest dairy herds. Herds were divided into 5 herd production categories. A linear score [LNS = ln(BTSCC/100,000)/0.693147 + 3] was calculated for each individual bulk tank SCC. For both the raw SCC and the transformed data, the mean and sigma were calculated using the statistical quality control individual measurement and moving range chart procedure of Statistical Analysis System. One hundred eighty-three herds of the 275 herds from the study data set were then randomly selected and the raw (method 1) and transformed (method 2) bulk tank SCC mean and sigma were used to develop models for predicting subclinical mastitis and new infection rate estimates. Herd production category was also included in all models as 5 dummy variables. Models were validated by calculating estimates of subclinical mastitis and new infection rates for the remaining 92 herds and plotting them against observed values of each of the dependents. Only herd production category and bulk tank SCC mean were significant and remained in the final models. High R2 values (0.83 and 0.81 for methods 1 and 2, respectively) indicated a strong correlation between the bulk tank SCC and herd's subclinical mastitis prevalence. The standard errors of the estimate were 4.02 and 4.28% for methods 1 and 2, respectively, and decreased with increasing herd production. As a case study, Shewhart Individual Measurement Charts were plotted from the bulk tank SCC to identify shifts in mastitis incidence. Four of 5 charts examined signaled a change in bulk tank SCC before
Directory of Open Access Journals (Sweden)
Iksoo Huh
Full Text Available Recent advances in genotyping methodologies have allowed genome-wide association studies (GWAS to accurately identify genetic variants that associate with common or pathological complex traits. Although most GWAS have focused on associations with single genetic variants, joint identification of multiple genetic variants, and how they interact, is essential for understanding the genetic architecture of complex phenotypic traits. Here, we propose an efficient stepwise method based on the Cochran-Mantel-Haenszel test (for stratified categorical data to identify causal joint multiple genetic variants in GWAS. This method combines the CMH statistic with a stepwise procedure to detect multiple genetic variants associated with specific categorical traits, using a series of associated I × J contingency tables and a null hypothesis of no phenotype association. Through a new stratification scheme based on the sum of minor allele count criteria, we make the method more feasible for GWAS data having sample sizes of several thousands. We also examine the properties of the proposed stepwise method via simulation studies, and show that the stepwise CMH test performs better than other existing methods (e.g., logistic regression and detection of associations by Markov blanket for identifying multiple genetic variants. Finally, we apply the proposed approach to two genomic sequencing datasets to detect linked genetic variants associated with bipolar disorder and obesity, respectively.
DEFF Research Database (Denmark)
Pedersen, Søren Nygaard
The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... been presented. Therefore, this study set out to contribute to the understanding and application of perceptual robust design. To achieve this, a state-of-the-art and current practice review was performed. From the review two main research problems were identified. Firstly, a lack of tools...... for perceptual robustness was found to overlap with the optimum for functional robustness and at most approximately 2.2% out of the 14.74% could be ascribed solely to the perceptual robustness optimisation. In conclusion, the thesis have offered a new perspective on robust design by merging robust design...
Directory of Open Access Journals (Sweden)
Resmi Gupta
2017-01-01
Full Text Available Aim. To examine the gestational glycemic profile and identify specific times during pregnancy that variability in glucose levels, measured by change in velocity and acceleration/deceleration of blood glucose fluctuations, is associated with delivery of a large-for-gestational-age (LGA baby, in women with type 1 diabetes. Methods. Retrospective analysis of capillary blood glucose levels measured multiple times daily throughout gestation in women with type 1 diabetes was performed using semiparametric mixed models. Results. Velocity and acceleration/deceleration in glucose levels varied across gestation regardless of delivery outcome. Compared to women delivering LGA babies, those delivering babies appropriate for gestational age exhibited significantly smaller rates of change and less variation in glucose levels between 180 days of gestation and birth. Conclusions. Use of innovative statistical methods enabled detection of gestational intervals in which blood glucose fluctuation parameters might influence the likelihood of delivering LGA baby in mothers with type 1 diabetes. Understanding dynamics and being able to visualize gestational changes in blood glucose are a potentially useful tool to assist care providers in determining the optimal timing to initiate continuous glucose monitoring.
Evans, Mark
2016-12-01
A new parametric approach, termed the Wilshire equations, offers the realistic potential of being able to accurately lift materials operating at in-service conditions from accelerated test results lasting no more than 5000 hours. The success of this approach can be attributed to a well-defined linear relationship that appears to exist between various creep properties and a log transformation of the normalized stress. However, these linear trends are subject to discontinuities, the number of which appears to differ from material to material. These discontinuities have until now been (1) treated as abrupt in nature and (2) identified by eye from an inspection of simple graphical plots of the data. This article puts forward a statistical test for determining the correct number of discontinuities present within a creep data set and a method for allowing these discontinuities to occur more gradually, so that the methodology is more in line with the accepted view as to how creep mechanisms evolve with changing test conditions. These two developments are fully illustrated using creep data sets on two steel alloys. When these new procedures are applied to these steel alloys, not only do they produce more accurate and realistic looking long-term predictions of the minimum creep rate, but they also lead to different conclusions about the mechanisms determining the rates of creep from those originally put forward by Wilshire.
Lim, T. C.
2016-12-01
Empirical evidence has shown linkages between urbanization, hydrological regime change, and degradation of water quality and aquatic habitat. Percent imperviousness, has long been suggested as the dominant source of these negative changes. However, recent research identifying alternative pathways of runoff production at the watershed scale have called into question percent impervious surface area's primacy in urban runoff production compared to other aspects of urbanization including change in vegetative cover, imported water and water leakages, and the presence of drainage infrastructure. In this research I show how a robust statistical methodology can detect evidence of variable source area (VSA)-type hydrologic response associated with incremental hydraulic connectivity in watersheds. I then use logistic regression to explore how evidence of VSA-type response relates to the physical and meterological characteristics of the watershed. I find that impervious surface area is highly correlated with development, but does not add significant explanatory power beyond percent developed in predicting VSA-type response. Other aspects of development morphology, including percent developed open space and type of drainage infrastructure also do not add to the explanatory power of undeveloped land in predicting VSA-type response. Within only developed areas, the effect of developed open space was found to be more similar to that of total impervious area than to undeveloped land. These findings were consistent when tested across a national cross-section of urbanized watersheds, a higher resolution dataset of Baltimore Metropolitan Area watersheds, and a subsample of watersheds confirmed not to be served by combined sewer systems. These findings suggest that land development policies that focus on lot coverage should be revisited, and more focus should be placed on preserving native vegetation and soil conditions alongside development.
Hoover, F. A.; Bowling, L. C.; Prokopy, L. S.
2015-12-01
Urban stormwater is an on-going management concern in municipalities of all sizes. In both combined or separated sewer systems, pollutants from stormwater runoff enter the natural waterway system during heavy rain events. Urban flooding during frequent and more intense storms are also a growing concern. Therefore, stormwater best-management practices (BMPs) are being implemented in efforts to reduce and manage stormwater pollution and overflow. The majority of BMP water quality studies focus on the small-scale, individual effects of the BMP, and the change in water quality directly from the runoff of these infrastructures. At the watershed scale, it is difficult to establish statistically whether or not these BMPs are making a difference in water quality, given that watershed scale monitoring is often costly and time consuming, relying on significant sources of funds, which a city may not have. Hence, there is a need to quantify the level of sampling needed to detect the water quality impact of BMPs at the watershed scale. In this study, a power analysis was performed on data from an urban watershed in Lafayette, Indiana, to determine the frequency of sampling required to detect a significant change in water quality measurements. Using the R platform, results indicate that detecting a significant change in watershed level water quality would require hundreds of weekly measurements, even when improvement is present. The second part of this study investigates whether the difficulty in demonstrating water quality change represents a barrier to adoption of stormwater BMPs. Semi-structured interviews of community residents and organizations in Chicago, IL are being used to investigate residents understanding of water quality and best management practices and identify their attitudes and perceptions towards stormwater BMPs. Second round interviews will examine how information on uncertainty in water quality improvements influences their BMP attitudes and perceptions.
International Nuclear Information System (INIS)
Rodionov, Andrei; Atwood, Corwin L.; Kirchsteiger, Christian; Patrik, Milan
2008-01-01
The paper presents some results of a case study on 'Demonstration of statistical approaches to identify the component's ageing by operational data analysis', which was done in the frame of the EC JRC Ageing PSA Network. Several techniques: visual evaluation, nonparametric and parametric hypothesis tests, were proposed and applied in order to demonstrate the capacity, advantages and limitations of statistical approaches to identify the component's ageing by operational data analysis. Engineering considerations are out of the scope of the present study
Robustness of Structural Systems
DEFF Research Database (Denmark)
Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.
2007-01-01
The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have...... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...
Pestman, Wiebe R
2009-01-01
This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.
Robust procedures in chemometrics
DEFF Research Database (Denmark)
Kotwa, Ewelina
properties of the analysed data. The broad theoretical background of robust procedures was given as a very useful supplement to the classical methods, and a new tool, based on robust PCA, aiming at identifying Rayleigh and Raman scatters in excitation-mission (EEM) data was developed. The results show...
Holen, Steven M.
2012-01-01
The purpose of this study was to review the history of North Dakota K-12 transportation funding system, identify how school districts are reimbursed for transportation expenses, and compare this information with fourteen other state transportation funding systems. North Dakota utilizes a block grant structure that has been in place since 1972 and…
Energy Technology Data Exchange (ETDEWEB)
Kyle, Jennifer E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Casey, Cameron P. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Stratton, Kelly G. [National Security Directorate, Pacific Northwest National Laboratory, Richland WA USA; Zink, Erika M. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Kim, Young-Mo [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Zheng, Xueyun [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Monroe, Matthew E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Weitz, Karl K. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Bloodsworth, Kent J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Orton, Daniel J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Ibrahim, Yehia M. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Moore, Ronald J. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Lee, Christine G. [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Research Service, Portland Veterans Affairs Medical Center, Portland OR USA; Pedersen, Catherine [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Orwoll, Eric [Department of Medicine, Bone and Mineral Unit, Oregon Health and Science University, Portland OR USA; Smith, Richard D. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Burnum-Johnson, Kristin E. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA; Baker, Erin S. [Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland WA USA
2017-02-05
The use of dried blood spots (DBS) has many advantages over traditional plasma and serum samples such as smaller blood volume required, storage at room temperature, and ability for sampling in remote locations. However, understanding the robustness of different analytes in DBS samples is essential, especially in older samples collected for longitudinal studies. Here we analyzed DBS samples collected in 2000-2001 and stored at room temperature and compared them to matched serum samples stored at -80°C to determine if they could be effectively used as specific time points in a longitudinal study following metabolic disease. Four hundred small molecules were identified in both the serum and DBS samples using gas chromatograph-mass spectrometry (GC-MS), liquid chromatography-MS (LC-MS) and LC-ion mobility spectrometry-MS (LC-IMS-MS). The identified polar metabolites overlapped well between the sample types, though only one statistically significant polar metabolite in a case-control study was conserved, indicating degradation occurs in the DBS samples affecting quantitation. Differences in the lipid identifications indicated that some oxidation occurs in the DBS samples. However, thirty-six statistically significant lipids correlated in both sample types indicating that lipid quantitation was more stable across the sample types.
Nair, Nishanth Ulhas; Sahu, Avinash Das; Bucher, Philipp; Moret, Bernard M E
2012-01-01
The advent of high-throughput technologies such as ChIP-seq has made possible the study of histone modifications. A problem of particular interest is the identification of regions of the genome where different cell types from the same organism exhibit different patterns of histone enrichment. This problem turns out to be surprisingly difficult, even in simple pairwise comparisons, because of the significant level of noise in ChIP-seq data. In this paper we propose a two-stage statistical method, called ChIPnorm, to normalize ChIP-seq data, and to find differential regions in the genome, given two libraries of histone modifications of different cell types. We show that the ChIPnorm method removes most of the noise and bias in the data and outperforms other normalization methods. We correlate the histone marks with gene expression data and confirm that histone modifications H3K27me3 and H3K4me3 act as respectively a repressor and an activator of genes. Compared to what was previously reported in the literature, we find that a substantially higher fraction of bivalent marks in ES cells for H3K27me3 and H3K4me3 move into a K27-only state. We find that most of the promoter regions in protein-coding genes have differential histone-modification sites. The software for this work can be downloaded from http://lcbb.epfl.ch/software.html.
Sriboonchitta, Songsak; Huynh, Van-Nam
2017-01-01
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
Directory of Open Access Journals (Sweden)
Emma Lightfoot
Full Text Available Oxygen isotope analysis of archaeological skeletal remains is an increasingly popular tool to study past human migrations. It is based on the assumption that human body chemistry preserves the δ18O of precipitation in such a way as to be a useful technique for identifying migrants and, potentially, their homelands. In this study, the first such global survey, we draw on published human tooth enamel and bone bioapatite data to explore the validity of using oxygen isotope analyses to identify migrants in the archaeological record. We use human δ18O results to show that there are large variations in human oxygen isotope values within a population sample. This may relate to physiological factors influencing the preservation of the primary isotope signal, or due to human activities (such as brewing, boiling, stewing, differential access to water sources and so on causing variation in ingested water and food isotope values. We compare the number of outliers identified using various statistical methods. We determine that the most appropriate method for identifying migrants is dependent on the data but is likely to be the IQR or median absolute deviation from the median under most archaeological circumstances. Finally, through a spatial assessment of the dataset, we show that the degree of overlap in human isotope values from different locations across Europe is such that identifying individuals' homelands on the basis of oxygen isotope analysis alone is not possible for the regions analysed to date. Oxygen isotope analysis is a valid method for identifying first-generation migrants from an archaeological site when used appropriately, however it is difficult to identify migrants using statistical methods for a sample size of less than c. 25 individuals. In the absence of local previous analyses, each sample should be treated as an individual dataset and statistical techniques can be used to identify migrants, but in most cases pinpointing a specific
Dean, Kimberly M; Grayhack, Elizabeth J
2012-12-01
We have developed a robust and sensitive method, called RNA-ID, to screen for cis-regulatory sequences in RNA using fluorescence-activated cell sorting (FACS) of yeast cells bearing a reporter in which expression of both superfolder green fluorescent protein (GFP) and yeast codon-optimized mCherry red fluorescent protein (RFP) is driven by the bidirectional GAL1,10 promoter. This method recapitulates previously reported progressive inhibition of translation mediated by increasing numbers of CGA codon pairs, and restoration of expression by introduction of a tRNA with an anticodon that base pairs exactly with the CGA codon. This method also reproduces effects of paromomycin and context on stop codon read-through. Five key features of this method contribute to its effectiveness as a selection for regulatory sequences: The system exhibits greater than a 250-fold dynamic range, a quantitative and dose-dependent response to known inhibitory sequences, exquisite resolution that allows nearly complete physical separation of distinct populations, and a reproducible signal between different cells transformed with the identical reporter, all of which are coupled with simple methods involving ligation-independent cloning, to create large libraries. Moreover, we provide evidence that there are sequences within a 9-nt library that cause reduced GFP fluorescence, suggesting that there are novel cis-regulatory sequences to be found even in this short sequence space. This method is widely applicable to the study of both RNA-mediated and codon-mediated effects on expression.
An Intercompany Perspective on Biopharmaceutical Drug Product Robustness Studies.
Morar-Mitrica, Sorina; Adams, Monica L; Crotts, George; Wurth, Christine; Ihnat, Peter M; Tabish, Tanvir; Antochshuk, Valentyn; DiLuzio, Willow; Dix, Daniel B; Fernandez, Jason E; Gupta, Kapil; Fleming, Michael S; He, Bing; Kranz, James K; Liu, Dingjiang; Narasimhan, Chakravarthy; Routhier, Eric; Taylor, Katherine D; Truong, Nobel; Stokes, Elaine S E
2018-02-01
The Biophorum Development Group (BPDG) is an industry-wide consortium enabling networking and sharing of best practices for the development of biopharmaceuticals. To gain a better understanding of current industry approaches for establishing biopharmaceutical drug product (DP) robustness, the BPDG-Formulation Point Share group conducted an intercompany collaboration exercise, which included a bench-marking survey and extensive group discussions around the scope, design, and execution of robustness studies. The results of this industry collaboration revealed several key common themes: (1) overall DP robustness is defined by both the formulation and the manufacturing process robustness; (2) robustness integrates the principles of quality by design (QbD); (3) DP robustness is an important factor in setting critical quality attribute control strategies and commercial specifications; (4) most companies employ robustness studies, along with prior knowledge, risk assessments, and statistics, to develop the DP design space; (5) studies are tailored to commercial development needs and the practices of each company. Three case studies further illustrate how a robustness study design for a biopharmaceutical DP balances experimental complexity, statistical power, scientific understanding, and risk assessment to provide the desired product and process knowledge. The BPDG-Formulation Point Share discusses identified industry challenges with regard to biopharmaceutical DP robustness and presents some recommendations for best practices. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Waldo, Stephen W; McCabe, James M; Kennedy, Kevin F; Zigler, Corwin M; Pinto, Duane S; Yeh, Robert W
2017-05-16
Public reporting of percutaneous coronary intervention (PCI) outcomes may create disincentives for physicians to provide care for critically ill patients, particularly at institutions with worse clinical outcomes. We thus sought to evaluate the procedural management and in-hospital outcomes of patients treated for acute myocardial infarction before and after a hospital had been publicly identified as a negative outlier. Using state reports, we identified hospitals that were recognized as negative PCI outliers in 2 states (Massachusetts and New York) from 2002 to 2012. State hospitalization files were used to identify all patients with an acute myocardial infarction within these states. Procedural management and in-hospital outcomes were compared among patients treated at outlier hospitals before and after public report of outlier status. Patients at nonoutlier institutions were used to control for temporal trends. Among 86 hospitals, 31 were reported as outliers for excess mortality. Outlier facilities were larger, treating more patients with acute myocardial infarction and performing more PCIs than nonoutlier hospitals ( P fashion (interaction P =0.50) after public report of outlier status. The likelihood of in-hospital mortality decreased at outlier institutions (RR, 0.83; 95% CI, 0.81-0.85) after public report, and to a lesser degree at nonoutlier institutions (RR, 0.90; 95% CI, 0.87-0.92; interaction P <0.001). Among patients that underwent PCI, in-hospital mortality decreased at outlier institutions after public recognition of outlier status in comparison with prior (RR, 0.72; 9% CI, 0.66-0.79), a decline that exceeded the reduction at nonoutlier institutions (RR, 0.87; 95% CI, 0.80-0.96; interaction P <0.001). Large hospitals with higher clinical volume are more likely to be designated as negative outliers. The rates of percutaneous revascularization increased similarly at outlier and nonoutlier institutions after report of outlier status. After outlier
Selimkhanov, J; Thompson, W C; Guo, J; Hall, K D; Musante, C J
2017-08-01
The design of well-powered in vivo preclinical studies is a key element in building the knowledge of disease physiology for the purpose of identifying and effectively testing potential antiobesity drug targets. However, as a result of the complexity of the obese phenotype, there is limited understanding of the variability within and between study animals of macroscopic end points such as food intake and body composition. This, combined with limitations inherent in the measurement of certain end points, presents challenges to study design that can have significant consequences for an antiobesity program. Here, we analyze a large, longitudinal study of mouse food intake and body composition during diet perturbation to quantify the variability and interaction of the key metabolic end points. To demonstrate how conclusions can change as a function of study size, we show that a simulated preclinical study properly powered for one end point may lead to false conclusions based on secondary end points. We then propose the guidelines for end point selection and study size estimation under different conditions to facilitate proper power calculation for a more successful in vivo study design.
DEFF Research Database (Denmark)
Gorm Hansen, Birgitte
their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...
Benci, Joseph L; Minn, Andy J; Vachani, Carolyn C; Bach, Christina; Arnold-Korzeniowski, Karen; Hampshire, Margaret K; Metz, James M; Hill-Kayser, Christine E
2018-01-01
Nearly 1 in 5 Americans will develop skin cancer, and as a result, survivors of skin cancer compose one of the largest groups of cancer survivors. Survivorship care plans (SCPs) are an important tool for improving patient outcomes and provide critical information to both survivors and health care professionals. Recent efforts have been made to expand SCP utilization; however, which patients currently receive SCPs is poorly understood. This study used 596 individuals with a diagnosis of melanoma (n = 391) or nonmelanoma skin cancer (n = 205) who had used an Internet-based SCP tool from May 2010 to December 2016 to model the patient and provider characteristics that determine SCP utilization. Survivors were predominantly white (95.3%) and female (56.5%). Survivors who received a treatment summary were more likely to also receive an SCP. University and nonuniversity cancer centers used SCPs at a higher rate than other care settings. Survivors whose care was managed by a team rather than just an individual physician were also more likely to receive an SCP. Survivors older than 70 years at diagnosis were almost twice as likely to receive a plan as survivors who were diagnosed at a younger age. With a convenience sample of skin cancer survivors, it is possible to model factors that predict the receipt of SCPs. Important variables include the diagnosis age, treatment setting, physician type, and treatment-summary utilization. A closer examination of these variables identified several disparities in care-plan use and, therefore, opportunities to improve the distribution of SCPs. Further validation in additional cohorts of survivors is necessary to confirm these conclusions. Cancer 2018;124:183-91. © 2017 American Cancer Society. © 2017 American Cancer Society.
On robust forecasting of autoregressive time series under censoring
Kharin, Y.; Badziahin, I.
2009-01-01
Problems of robust statistical forecasting are considered for autoregressive time series observed under distortions generated by interval censoring. Three types of robust forecasting statistics are developed; meansquare risk is evaluated for the developed forecasting statistics. Numerical results are given.
Directory of Open Access Journals (Sweden)
Eduardo Fukutani
2018-05-01
Full Text Available The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.
Fukutani, Eduardo; Rodrigues, Moreno; Kasprzykowski, José Irahe; Araujo, Cintia Figueiredo de; Paschoal, Alexandre Rossi; Ramos, Pablo Ivan Pereira; Fukutani, Kiyoshi Ferreira; Queiroz, Artur Trancoso Lopo de
2018-01-01
The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this "infection" gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.
A Noise Robust Statistical Texture Model
DEFF Research Database (Denmark)
Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus
2002-01-01
Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise......This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...
Robustness, Diagnostics, Computing and Graphics in Statistics
1990-01-01
seto his collection at nuformation. ruciL.ong suggestions for reducing this burden to Washington iieadcuarters Services . Directorate or information...Lewis Cornell University Keaing Lu Georgia Institute of Technology Mary Silber UC, Berkeley Matthew W. Stafford Loyola University Mary Lou Zeeman UC...wavefronts in excitable media are determined by the manner of recovery to the rest state. The distance between a pair of wavefronts tends to lock at one of
Smylie, Janet; Firestone, Michelle
Canada is known internationally for excellence in both the quality and public policy relevance of its health and social statistics. There is a double standard however with respect to the relevance and quality of statistics for Indigenous populations in Canada. Indigenous specific health and social statistics gathering is informed by unique ethical, rights-based, policy and practice imperatives regarding the need for Indigenous participation and leadership in Indigenous data processes throughout the spectrum of indicator development, data collection, management, analysis and use. We demonstrate how current Indigenous data quality challenges including misclassification errors and non-response bias systematically contribute to a significant underestimate of inequities in health determinants, health status, and health care access between Indigenous and non-Indigenous people in Canada. The major quality challenge underlying these errors and biases is the lack of Indigenous specific identifiers that are consistent and relevant in major health and social data sources. The recent removal of an Indigenous identity question from the Canadian census has resulted in further deterioration of an already suboptimal system. A revision of core health data sources to include relevant, consistent, and inclusive Indigenous self-identification is urgently required. These changes need to be carried out in partnership with Indigenous peoples and their representative and governing organizations.
International Nuclear Information System (INIS)
Kertzscher, Gustavo; Andersen, Claus E.; Siebert, Frank-Andre; Nielsen, Soren Kynde; Lindegaard, Jacob C.; Tanderup, Kari
2011-01-01
Background and purpose: The feasibility of a real-time in vivo dosimeter to detect errors has previously been demonstrated. The purpose of this study was to: (1) quantify the sensitivity of the dosimeter to detect imposed treatment errors under well controlled and clinically relevant experimental conditions, and (2) test a new statistical error decision concept based on full uncertainty analysis. Materials and methods: Phantom studies of two gynecological cancer PDR and one prostate cancer HDR patient treatment plans were performed using tandem ring applicators or interstitial needles. Imposed treatment errors, including interchanged pairs of afterloader guide tubes and 2-20 mm source displacements, were monitored using a real-time fiber-coupled carbon doped aluminum oxide (Al 2 O 3 :C) crystal dosimeter that was positioned in the reconstructed tumor region. The error detection capacity was evaluated at three dose levels: dwell position, source channel, and fraction. The error criterion incorporated the correlated source position uncertainties and other sources of uncertainty, and it was applied both for the specific phantom patient plans and for a general case (source-detector distance 5-90 mm and position uncertainty 1-4 mm). Results: Out of 20 interchanged guide tube errors, time-resolved analysis identified 17 while fraction level analysis identified two. Channel and fraction level comparisons could leave 10 mm dosimeter displacement errors unidentified. Dwell position dose rate comparisons correctly identified displacements ≥5 mm. Conclusion: This phantom study demonstrates that Al 2 O 3 :C real-time dosimetry can identify applicator displacements ≥5 mm and interchanged guide tube errors during PDR and HDR brachytherapy. The study demonstrates the shortcoming of a constant error criterion and the advantage of a statistical error criterion.
International Nuclear Information System (INIS)
Zhang Changbo; Wu Longhua; Luo Yongming; Zhang Haibo; Christie, Peter
2008-01-01
Principal components analysis (PCA) and correlation analysis were used to estimate the contribution of four components related to pollutant sources on the total variation in concentrations of Cu, Zn, Pb, Cd, As, Se, Hg, Fe and Mn in surface soil samples from a valley in east China with numerous copper and zinc smelters. Results indicate that when carrying out source identification of inorganic pollutants their tendency to migrate in soils may result in differences between the pollutant composition of the source and the receptor soil, potentially leading to errors in the characterization of pollutants using multivariate statistics. The stability and potential migration or movement of pollutants in soils must therefore be taken into account. Soil physicochemical properties may offer additional useful information. Two different mechanisms have been hypothesized for correlations between soil heavy metal concentrations and soil organic matter content and these may be helpful in interpreting the statistical analysis. - Principal components analysis with Varimax rotation can help identify sources of soil inorganic pollutants but pollutant migration and soil properties can exert important effects
Directory of Open Access Journals (Sweden)
Elise eVaumourin
2014-05-01
Full Text Available A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e. the generalized chi-square, the network and the multinomial GLM approaches to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: 1 rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and 2 bovine population infected with Theileria sp. and Babesia sp.. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unravelling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions
Marković, Snežana; Kerč, Janez; Horvat, Matej
2017-03-01
We are presenting a new approach of identifying sources of variability within a manufacturing process by NIR measurements of samples of intermediate material after each consecutive unit operation (interprocess NIR sampling technique). In addition, we summarize the development of a multivariate statistical process control (MSPC) model for the production of enteric-coated pellet product of the proton-pump inhibitor class. By developing provisional NIR calibration models, the identification of critical process points yields comparable results to the established MSPC modeling procedure. Both approaches are shown to lead to the same conclusion, identifying parameters of extrusion/spheronization and characteristics of lactose that have the greatest influence on the end-product's enteric coating performance. The proposed approach enables quicker and easier identification of variability sources during manufacturing process, especially in cases when historical process data is not straightforwardly available. In the presented case the changes of lactose characteristics are influencing the performance of the extrusion/spheronization process step. The pellet cores produced by using one (considered as less suitable) lactose source were on average larger and more fragile, leading to consequent breakage of the cores during subsequent fluid bed operations. These results were confirmed by additional experimental analyses illuminating the underlying mechanism of fracture of oblong pellets during the pellet coating process leading to compromised film coating.
Directory of Open Access Journals (Sweden)
Yongmei Sun
Full Text Available RNA editing is one of the post- or co-transcriptional processes that can lead to amino acid substitutions in protein sequences, alternative pre-mRNA splicing, and changes in gene expression levels. Although several methods have been suggested to identify RNA editing sites, there remains challenges to be addressed in distinguishing true RNA editing sites from its counterparts on genome and technical artifacts. In addition, there lacks a software framework to identify and visualize potential RNA editing sites. Here, we presented a software - 'RED' (RNA Editing sites Detector - for the identification of RNA editing sites by integrating multiple rule-based and statistical filters. The potential RNA editing sites can be visualized at the genome and the site levels by graphical user interface (GUI. To improve performance, we used MySQL database management system (DBMS for high-throughput data storage and query. We demonstrated the validity and utility of RED by identifying the presence and absence of C→U RNA-editing sites experimentally validated, in comparison with REDItools, a command line tool to perform high-throughput investigation of RNA editing. In an analysis of a sample data-set with 28 experimentally validated C→U RNA editing sites, RED had sensitivity and specificity of 0.64 and 0.5. In comparison, REDItools had a better sensitivity (0.75 but similar specificity (0.5. RED is an easy-to-use, platform-independent Java-based software, and can be applied to RNA-seq data without or with DNA sequencing data. The package is freely available under the GPLv3 license at http://github.com/REDetector/RED or https://sourceforge.net/projects/redetector.
Sun, Yongmei; Li, Xing; Wu, Di; Pan, Qi; Ji, Yuefeng; Ren, Hong; Ding, Keyue
2016-01-01
RNA editing is one of the post- or co-transcriptional processes that can lead to amino acid substitutions in protein sequences, alternative pre-mRNA splicing, and changes in gene expression levels. Although several methods have been suggested to identify RNA editing sites, there remains challenges to be addressed in distinguishing true RNA editing sites from its counterparts on genome and technical artifacts. In addition, there lacks a software framework to identify and visualize potential RNA editing sites. Here, we presented a software - 'RED' (RNA Editing sites Detector) - for the identification of RNA editing sites by integrating multiple rule-based and statistical filters. The potential RNA editing sites can be visualized at the genome and the site levels by graphical user interface (GUI). To improve performance, we used MySQL database management system (DBMS) for high-throughput data storage and query. We demonstrated the validity and utility of RED by identifying the presence and absence of C→U RNA-editing sites experimentally validated, in comparison with REDItools, a command line tool to perform high-throughput investigation of RNA editing. In an analysis of a sample data-set with 28 experimentally validated C→U RNA editing sites, RED had sensitivity and specificity of 0.64 and 0.5. In comparison, REDItools had a better sensitivity (0.75) but similar specificity (0.5). RED is an easy-to-use, platform-independent Java-based software, and can be applied to RNA-seq data without or with DNA sequencing data. The package is freely available under the GPLv3 license at http://github.com/REDetector/RED or https://sourceforge.net/projects/redetector.
Robust loss functions for boosting.
Kanamori, Takafumi; Takenouchi, Takashi; Eguchi, Shinto; Murata, Noboru
2007-08-01
Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting algorithms robust against extreme outliers. Next, the truncation of loss functions is applied to contamination models that describe the occurrence of mislabels near decision boundaries. Numerical experiments illustrate that the proposed loss functions derived from the contamination models are useful for handling highly noisy data in comparison with other loss functions.
Johnson, Matthew G; Brown, Sheryll; Archer, Pam; Wendelboe, Aaron; Magzamen, Sheryl; Bradley, Kristy K
2016-10-01
Approximately 660 deaths occur annually in the United States associated with excess natural heat. A record heat wave in Oklahoma during 2011 generated increased interest concerning heat-related mortality among public health preparedness partners. We aimed to improve surveillance for heat-related mortality and better characterize heat-related deaths in Oklahoma during 1990-2011, and to enhance public health messaging during future heat emergencies. Heat-related deaths were identified by querying vital statistics (VS) and medical examiner (ME) data during 1990-2011. Case inclusion criteria were developed by using heat-related International Classification of Diseases codes, cause-of-death nomenclature, and ME investigation narrative. We calculated sensitivity and predictive value positive (PVP) for heat-related mortality surveillance by using VS and ME data and performed a descriptive analysis. During the study period, 364 confirmed and probable heat-related deaths were identified when utilizing both data sets. ME reports had 87% sensitivity and 74% PVP; VS reports had 80% sensitivity and 52% PVP. Compared to Oklahoma's general population, decedents were disproportionately male (67% vs. 49%), aged ≥65 years (46% vs. 14%), and unmarried (78% vs. 47%). Higher rates of heat-related mortality were observed among Blacks. Of 95 decedents with available information, 91 (96%) did not use air conditioning. Linking ME and VS data sources together and using narrative description for case classification allows for improved case ascertainment and surveillance data quality. Males, Blacks, persons aged ≥65 years, unmarried persons, and those without air conditioning carry a disproportionate burden of the heat-related deaths in Oklahoma. Published by Elsevier Inc.
Llope, W. J.; STAR Collaboration
2013-10-01
Specific products of the statistical moments of the multiplicity distributions of identified particles can be directly compared to susceptibility ratios obtained from lattice QCD calculations. They may also diverge for nuclear systems formed close to a possible QCD critical point due to the phenomenon of critical opalescence. Of particular interest are the moments products for net-protons, net-kaons, and net-charge, as these are considered proxies for conserved quantum numbers. The moments products have been measured by the STAR experiment for Au+Au collisions at seven beam energies ranging from 7.7 to 200 GeV. In this presentation, the experimental results are compared to data-based calculations in which the intra-event correlations of the numbers of positive and negative particles are broken by construction. The importance of intra-event correlations to the moments products values for net-protons, net-kaons, and net-charge can thus be evaluated. Work supported by the U.S. Dept of Energy under grant DE-PS02-09ER09.
Energy Technology Data Exchange (ETDEWEB)
Wendelberger, Laura Jean [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-08-08
In large datasets, it is time consuming or even impossible to pick out interesting images. Our proposed solution is to find statistics to quantify the information in each image and use those to identify and pick out images of interest.
Robust estimation and hypothesis testing
Tiku, Moti L
2004-01-01
In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomali...
International Nuclear Information System (INIS)
Fournel, Thierry; Coltuc, Daniela
2010-01-01
Designed to maximize information transmission in the presence of noise, independent component analysis (ICA) could appear in certain circumstances as a statistics-based tool for robust visual hashing. Several ICA-based scenarios can attempt to reach this goal. A first one is here considered.
Facial Symmetry in Robust Anthropometrics
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 57, č. 3 (2012), s. 691-698 ISSN 0022-1198 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : forensic science * anthropology * robust image analysis * correlation analysis * multivariate data * classification Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.244, year: 2012
Directory of Open Access Journals (Sweden)
Marek Hicar
2004-01-01
Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.
Applying contemporary statistical techniques
Wilcox, Rand R
2003-01-01
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advanc
MacKenzie, Dana
2004-01-01
The drawbacks of using 19th-century mathematics in physics and astronomy are illustrated. To continue with the expansion of the knowledge about the cosmos, the scientists will have to come in terms with modern statistics. Some researchers have deliberately started importing techniques that are used in medical research. However, the physicists need to identify the brand of statistics that will be suitable for them, and make a choice between the Bayesian and the frequentists approach. (Edited abstract).
Methods for robustness programming
Olieman, N.J.
2008-01-01
Robustness of an object is defined as the probability that an object will have properties as required. Robustness Programming (RP) is a mathematical approach for Robustness estimation and Robustness optimisation. An example in the context of designing a food product, is finding the best composition
Star, L.
2008-01-01
The aim of the project ‘The genetics of robustness in laying hens’ was to investigate nature and regulation of robustness in laying hens under sub-optimal conditions and the possibility to increase robustness by using animal breeding without loss of production. At the start of the project, a robust
Understanding Statistics - Cancer Statistics
Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.
Implicitly Weighted Methods in Robust Image Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2012-01-01
Roč. 44, č. 3 (2012), s. 449-462 ISSN 0924-9907 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robustness * high breakdown point * outlier detection * robust correlation analysis * template matching * face recognition Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.767, year: 2012
Testing Heteroscedasticity in Robust Regression
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2011-01-01
Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf
Highly Robust Methods in Data Mining
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2013-01-01
Roč. 8, č. 1 (2013), s. 9-24 ISSN 1452-4864 Institutional support: RVO:67985807 Keywords : data mining * robust statistics * high-dimensional data * cluster analysis * logistic regression * neural networks Subject RIV: BB - Applied Statistics, Operational Research
International Nuclear Information System (INIS)
Gu Yangguang; Wang, Zhao-Hui; Lu Songhui; Jiang Shijun; Mu Dehai; Shu Yonghong
2012-01-01
Growing concerns surround the mid Guangdong coasts, one of China’s fastest and developing economical regions. To study the environmental impacts of economic and industrial development, we measured ten metallic elements (Hg, Pb, Cu, Zn, Fe, Al, Ni, Sr, Li, and Co) in surface sediments from nineteen stations in three bays. All these metals showed concentrations substantially higher than their background values, suggesting possible anthropogenic pollution. Highest metal levels were close to the nuclear power plants likely as a result of nuclear waste discharges. Results revealed that Hg, Pb, and Sr largely originated from human activities, while Cu, Ni, Co, Al, and Fe mainly from natural rock weathering. Two types of anthropogenic sources were identified through a principal component analysis, one from shipping industry, port transport service and nuclear power plants, and the other from municipal sewage and coal power plant. - Highlights: ► Ten metallic elements in surface sediments from mid Guangdong coasts were measured. ► High metal levels occurred close to the nuclear power plants. ► Hg, Pb and Sr mainly originated from human activities. ► Two types of anthropogenic metallic sources were identified in this region. - Hot spots of metallic elements were close to the nuclear power plants. Industrial and municipal discharges were the main anthropogenic metallic source.
Parshad, Rana D; McGregor, Stephen J; Busa, Michael A; Skufca, Joseph D; Bollt, Erik
2012-01-01
Control entropy (CE) is a complexity analysis suitable for dynamic, non-stationary conditions which allows the inference of the control effort of a dynamical system generating the signal. These characteristics make CE a highly relevant time varying quantity relevant to the dynamic physiological responses associated with running. Using High Resolution Accelerometry (HRA) signals we evaluate here constraints of running gait, from two different groups of runners, highly trained collegiate and untrained runners. To this end,we further develop the control entropy (CE) statistic to allow for group analysis to examine the non-linear characteristics of movement patterns in highly trained runners with those of untrained runners, to gain insight regarding gaits that are optimal for running. Specifically, CE develops response time series of individuals descriptive of the control effort; a group analysis of these shapes developed here uses Karhunen Loeve Analysis (KL) modes of these time series which are compared between groups by application of a Hotelling T² test to these group response shapes. We find that differences in the shape of the CE response exist within groups, between axes for untrained runners (vertical vs anterior-posterior and mediolateral vs anterior-posterior) and trained runners (mediolateral vs anterior-posterior). Also shape differences exist between groups by axes (vertical vs mediolateral). Further, the CE, as a whole, was higher in each axis in trained vs untrained runners. These results indicate that the approach can provide unique insight regarding the differing constraints on running gait in highly trained and untrained runners when running under dynamic conditions. Further, the final point indicates trained runners are less constrained than untrained runners across all running speeds.
Shah, Sohil Atul; Koltun, Vladlen
2017-09-12
Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.
DEFF Research Database (Denmark)
Arnbjerg-Nielsen, Karsten; Funder, S. G.; Madsen, H.
2015-01-01
Climate analogues, also denoted Space-For-Time, may be used to identify regions where the present climatic conditions resemble conditions of a past or future state of another location or region based on robust climate variable statistics in combination with projections of how these statistics cha...
Directory of Open Access Journals (Sweden)
Rojas Flavio
2007-07-01
Full Text Available Abstract Background This research concerns Araucanía, often called the Ninth Region, the poorest region of Chile where inequalities are most extreme. Araucanía hasn't enjoyed the economic success Chile achieved when the country returned to democracy in 1990. The Ninth Region also has the largest ethnic Mapuche population, located in rural areas and attached to small agricultural properties. Written and oral histories of diseases have been the most frequently used methods to explore the links between an ancestral population's perception of health conditions and their deprived environments. With census data and hospital records, it is now possible to incorporate statistical data about the links between poverty and disease among ethnic communities and compare results with non-Mapuche population. Data sources Hospital discharge records from Health Services North N = 24,126 patients, year 2003, and 7 hospitals, Health Services South (N = 81,780 patients and 25 hospitals; CAS-2/Family records (N = 527,539 individuals, 439 neighborhoods, 32 Comunas. Methods Given the over-dispersion of data and the clustered nature of observations, we used the global Moran's I and General G Gettis-Ord procedures to test spatial dependence. These tests confirmed the clusters of disease and the need to use spatial regression within a General Linear Mixed Model perspective. Results Health outcomes indicate significantly higher morbidity rates for the Mapuche compared to non-Mapuche in both age groups Mapuches than non-Mapuches for the entire Ninth Region and for all age groups. Mortality caused by respiratory infections is higher among Mapuches than non-Mapuches in all age-groups. A major finding is the link between poverty and respiratory infections. Conclusion Poverty is significantly associated with respiratory infections in the population of Chile's Ninth Region. High deprivation areas are associated with poverty, and poverty is a predictor of respiratory infections
Rojas, Flavio
2007-07-02
This research concerns Araucanía, often called the Ninth Region, the poorest region of Chile where inequalities are most extreme. Araucanía hasn't enjoyed the economic success Chile achieved when the country returned to democracy in 1990. The Ninth Region also has the largest ethnic Mapuche population, located in rural areas and attached to small agricultural properties. Written and oral histories of diseases have been the most frequently used methods to explore the links between an ancestral population's perception of health conditions and their deprived environments. With census data and hospital records, it is now possible to incorporate statistical data about the links between poverty and disease among ethnic communities and compare results with non-Mapuche population. Hospital discharge records from Health Services North N = 24,126 patients, year 2003, and 7 hospitals), Health Services South (N = 81,780 patients and 25 hospitals); CAS-2/Family records (N = 527,539 individuals, 439 neighborhoods, 32 Comunas). Given the over-dispersion of data and the clustered nature of observations, we used the global Moran's I and General G Gettis-Ord procedures to test spatial dependence. These tests confirmed the clusters of disease and the need to use spatial regression within a General Linear Mixed Model perspective. Health outcomes indicate significantly higher morbidity rates for the Mapuche compared to non-Mapuche in both age groups Mapuches than non-Mapuches for the entire Ninth Region and for all age groups. Mortality caused by respiratory infections is higher among Mapuches than non-Mapuches in all age-groups. A major finding is the link between poverty and respiratory infections. Poverty is significantly associated with respiratory infections in the population of Chile's Ninth Region. High deprivation areas are associated with poverty, and poverty is a predictor of respiratory infections. Mapuches are at higher risk of deaths caused by respiratory infections in
Pivato, Marcus
2013-01-01
We show that, in a sufficiently large population satisfying certain statistical regularities, it is often possible to accurately estimate the utilitarian social welfare function, even if we only have very noisy data about individual utility functions and interpersonal utility comparisons. In particular, we show that it is often possible to identify an optimal or close-to-optimal utilitarian social choice using voting rules such as the Borda rule, approval voting, relative utilitarianism, or a...
DEFF Research Database (Denmark)
Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard
2011-01-01
In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...... the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...
Doppelhofer, Gernot; Weeks, Melvyn
2011-01-01
This paper investigates the robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsi- monious mixture modeling that allows for fat-tailed errors compared to the normal benchmark case. Applying robust model averaging to growth determinants, the paper finds that eight out of eighteen variables found to be significantly related to economic growth ...
Bishop , Matt; Elliott , Chip
2011-01-01
Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.
What is it to be sturdy (robust)?
DEFF Research Database (Denmark)
Nielsen, Niss Skov; Zwisler, Lars Pagter; Bojsen, Ann Kristina Mikkelsen
Purpose: This paper intends to give a first insight into the concept of being "sturdy/robust"; To develop and test a Danish model of how to measure sturdi-ness/robustness; To test the scale's ability to identify people in emergency situa-tions who have high risk of developing psychological illness....
How to Reduce Dimensionality of Data: Robustness Point of View
Czech Academy of Sciences Publication Activity Database
Kalina, Jan; Rensová, D.
2015-01-01
Roč. 10, č. 1 (2015), s. 131-140 ISSN 1452-4864 R&D Projects: GA ČR GA13-17187S Institutional support: RVO:67985807 Keywords : data analysis * dimensionality reduction * robust statistics * principal component analysis * robust classification analysis Subject RIV: BB - Applied Statistics, Operational Research
Comparing Four Instructional Techniques for Promoting Robust Knowledge
Richey, J. Elizabeth; Nokes-Malach, Timothy J.
2015-01-01
Robust knowledge serves as a common instructional target in academic settings. Past research identifying characteristics of experts' knowledge across many domains can help clarify the features of robust knowledge as well as ways of assessing it. We review the expertise literature and identify three key features of robust knowledge (deep,…
International Nuclear Information System (INIS)
Lim, Gyeong Hui
2008-03-01
This book consists of 15 chapters, which are basic conception and meaning of statistical thermodynamics, Maxwell-Boltzmann's statistics, ensemble, thermodynamics function and fluctuation, statistical dynamics with independent particle system, ideal molecular system, chemical equilibrium and chemical reaction rate in ideal gas mixture, classical statistical thermodynamics, ideal lattice model, lattice statistics and nonideal lattice model, imperfect gas theory on liquid, theory on solution, statistical thermodynamics of interface, statistical thermodynamics of a high molecule system and quantum statistics
Robust matching for voice recognition
Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.
1994-10-01
This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.
Robustness Beamforming Algorithms
Directory of Open Access Journals (Sweden)
Sajad Dehghani
2014-04-01
Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.
Statistical Pattern Recognition
Webb, Andrew R
2011-01-01
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,
Directory of Open Access Journals (Sweden)
Klara Rosta
Full Text Available Genetic variation in human maternal DNA contributes to the susceptibility for development of gestational diabetes mellitus (GDM.We assessed 77 maternal single nucleotide gene polymorphisms (SNPs for associations with GDM or plasma glucose levels at OGTT in pregnancy.960 pregnant women (after dropouts 820: case/control: m99'WHO: 303/517, IADPSG: 287/533 were enrolled in two countries into this case-control study. After genomic DNA isolation the 820 samples were collected in a GDM biobank and assessed using KASP (LGC Genomics genotyping assay. Logistic regression risk models were used to calculate ORs according to IADPSG/m'99WHO criteria based on standard OGTT values.The most important risk alleles associated with GDM were rs10830963/G of MTNR1B (OR = 1.84/1.64 [IADPSG/m'99WHO], p = 0.0007/0.006, rs7754840/C (OR = 1.51/NS, p = 0.016 of CDKAL1 and rs1799884/T (OR = 1.4/1.56, p = 0.04/0.006 of GCK. The rs13266634/T (SLC30A8, OR = 0.74/0.71, p = 0.05/0.02 and rs7578326/G (LOC646736/IRS1, OR = 0.62/0.60, p = 0.001/0.006 variants were associated with lower risk to develop GDM. Carrying a minor allele of rs10830963 (MTNR1B; rs7903146 (TCF7L2; rs1799884 (GCK SNPs were associated with increased plasma glucose levels at routine OGTT.We confirmed the robust association of MTNR1B rs10830963/G variant with GDM binary and glycemic traits in this Caucasian case-control study. As novel associations we report the minor, G allele of the rs7578326 SNP in the LOC646736/IRS1 region as a significant and the rs13266634/T SNP (SLC30A8 as a suggestive protective variant against GDM development. Genetic susceptibility appears to be more preponderant in individuals who meet both the modified 99'WHO and the IADPSG GDM diagnostic criteria.
Robustness Metrics: Consolidating the multiple approaches to quantify Robustness
DEFF Research Database (Denmark)
Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.
2016-01-01
robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...
Defining robustness protocols: a method to include and evaluate robustness in clinical plans
International Nuclear Information System (INIS)
McGowan, S E; Albertini, F; Lomax, A J; Thomas, S J
2015-01-01
We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties. (paper)
Defining robustness protocols: a method to include and evaluate robustness in clinical plans
McGowan, S. E.; Albertini, F.; Thomas, S. J.; Lomax, A. J.
2015-04-01
We aim to define a site-specific robustness protocol to be used during the clinical plan evaluation process. Plan robustness of 16 skull base IMPT plans to systematic range and random set-up errors have been retrospectively and systematically analysed. This was determined by calculating the error-bar dose distribution (ebDD) for all the plans and by defining some metrics used to define protocols aiding the plan assessment. Additionally, an example of how to clinically use the defined robustness database is given whereby a plan with sub-optimal brainstem robustness was identified. The advantage of using different beam arrangements to improve the plan robustness was analysed. Using the ebDD it was found range errors had a smaller effect on dose distribution than the corresponding set-up error in a single fraction, and that organs at risk were most robust to the range errors, whereas the target was more robust to set-up errors. A database was created to aid planners in terms of plan robustness aims in these volumes. This resulted in the definition of site-specific robustness protocols. The use of robustness constraints allowed for the identification of a specific patient that may have benefited from a treatment of greater individuality. A new beam arrangement showed to be preferential when balancing conformality and robustness for this case. The ebDD and error-bar volume histogram proved effective in analysing plan robustness. The process of retrospective analysis could be used to establish site-specific robustness planning protocols in proton therapy. These protocols allow the planner to determine plans that, although delivering a dosimetrically adequate dose distribution, have resulted in sub-optimal robustness to these uncertainties. For these cases the use of different beam start conditions may improve the plan robustness to set-up and range uncertainties.
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2008-01-01
This paper describes the background of the robustness requirements implemented in the Danish Code of Practice for Safety of Structures and in the Danish National Annex to the Eurocode 0, see (DS-INF 146, 2003), (DS 409, 2006), (EN 1990 DK NA, 2007) and (Sørensen and Christensen, 2006). More...... frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new structures essential....... According to Danish design rules robustness shall be documented for all structures in high consequence class. The design procedure to document sufficient robustness consists of: 1) Review of loads and possible failure modes / scenarios and determination of acceptable collapse extent; 2) Review...
DEFF Research Database (Denmark)
Vrouwenvelder, T.; Sørensen, John Dalsgaard
2009-01-01
After the collapse of the World Trade Centre towers in 2001 and a number of collapses of structural systems in the beginning of the century, robustness of structural systems has gained renewed interest. Despite many significant theoretical, methodical and technological advances, structural...... of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its uantification. A European COST action TU 601 on ‘Robustness of structures' has started in 2007...... by a group of members of the CSS. This paper describes the ongoing work in this action, with emphasis on the development of a theoretical and risk based quantification and optimization procedure on the one side and a practical pre-normative guideline on the other....
Robust Approaches to Forecasting
Jennifer Castle; David Hendry; Michael P. Clements
2014-01-01
We investigate alternative robust approaches to forecasting, using a new class of robust devices, contrasted with equilibrium correction models. Their forecasting properties are derived facing a range of likely empirical problems at the forecast origin, including measurement errors, implulses, omitted variables, unanticipated location shifts and incorrectly included variables that experience a shift. We derive the resulting forecast biases and error variances, and indicate when the methods ar...
Robustness - theoretical framework
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.
2010-01-01
More frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure combined with increased requirements to efficiency in design and execution followed by increased risk of human errors has made the need of requirements to robustness of new struct...... of this fact sheet is to describe a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines....
Qualitative Robustness in Estimation
Directory of Open Access Journals (Sweden)
Mohammed Nasser
2012-07-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Times New Roman","serif";} Qualitative robustness, influence function, and breakdown point are three main concepts to judge an estimator from the viewpoint of robust estimation. It is important as well as interesting to study relation among them. This article attempts to present the concept of qualitative robustness as forwarded by first proponents and its later development. It illustrates intricacies of qualitative robustness and its relation with consistency, and also tries to remove commonly believed misunderstandings about relation between influence function and qualitative robustness citing some examples from literature and providing a new counter-example. At the end it places a useful finite and a simulated version of qualitative robustness index (QRI. In order to assess the performance of the proposed measures, we have compared fifteen estimators of correlation coefficient using simulated as well as real data sets.
Hudig, Dorothy; Hunter, Kenneth W; Diamond, W John; Redelman, Doug
2014-03-01
This study was designed to improve identification of human blood monocytes by using antibodies to molecules that occur consistently on all stages of monocyte development and differentiation. We examined blood samples from 200 healthy adults without clinically diagnosed immunological abnormalities by flow cytometry (FCM) with multiple combinations of antibodies and with a hematology analyzer (Beckman LH750). CD91 (α2 -macroglobulin receptor) was expressed only by monocytes and to a consistent level among subjects [mean median fluorescence intensity (MFI) = 16.2 ± 3.2]. Notably, only 85.7 ± 5.82% of the CD91(+) monocytes expressed high levels of the classical monocyte marker CD14, with some CD91(+) CD16(+) cells having negligible CD14, indicating that substantial FCM under-counts will occur when monocytes are identified by high CD14. CD33 (receptor for sialyl conjugates) was co-expressed with CD91 on monocytes but CD33 expression varied by nearly ten-fold among subjects (mean MFI = 17.4 ± 7.7). In comparison to FCM analyses, the hematology analyzer systematically over-counted monocytes and eosinophils while lymphocyte and neutrophil differential values generally agreed with FCM methods. CD91 is a better marker to identify monocytes than CD14 or CD33. Furthermore, FCM (with anti-CD91) identifies monocytes better than a currently used clinical CBC instrument. Use of anti-CD91 together with anti-CD14 and anti-CD16 supports the identification of the diagnostically significant monocyte populations with variable expression of CD14 and CD16. Copyright © 2013 Clinical Cytometry Society.
... What Is Cancer? Cancer Statistics Cancer Disparities Cancer Statistics Cancer has a major impact on society in ... success of efforts to control and manage cancer. Statistics at a Glance: The Burden of Cancer in ...
Introduction to Bayesian statistics
Bolstad, William M
2017-01-01
There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this Third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian staistics. The author continues to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inferenfe cfor discrete random variables, bionomial proprotion, Poisson, normal mean, and simple linear regression. In addition, newly-developing topics in the field are presented in four new chapters: Bayesian inference with unknown mean and variance; Bayesian inference for Multivariate Normal mean vector; Bayesian inference for Multiple Linear RegressionModel; and Computati...
A Robust Alternative to the Normal Distribution.
1982-07-07
for any Purpose of the United States Governuent DEPARTMENT OF STATISTICS t -, STANFORD UIVERSITY I STANFORD, CALIFORNIA A Robust Alternative to the...Stanford University Technical Report No. 3. [5] Bhattacharya, S. K. (1966). A Modified Bessel Function lodel in Life Testing. Metrika 10, 133-144
Some Diagnostic Tools in Robust Econometrics
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2011-01-01
Roč. 50, č. 2 (2011), s. 55-67 ISSN 0231-9721 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * autocorrelated errors * heteroscedastic regression * instrumental variables * least weighted squares Subject RIV: BB - Applied Statistics, Operational Research http://dml.cz/handle/10338.dmlcz/141754
Statistical Analysis of Big Data on Pharmacogenomics
Fan, Jianqing; Liu, Han
2013-01-01
This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905
Robust methods for multivariate data analysis A1
DEFF Research Database (Denmark)
Frosch, Stina; Von Frese, J.; Bro, Rasmus
2005-01-01
Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...
2013-01-01
This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...
DEFF Research Database (Denmark)
Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas
2014-01-01
Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...
Robust Self Tuning Controllers
DEFF Research Database (Denmark)
Poulsen, Niels Kjølstad
1985-01-01
The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...
Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert
2008-01-01
We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This
Robustness Envelopes of Networks
Trajanovski, S.; Martín-Hernández, J.; Winterbach, W.; Van Mieghem, P.
2013-01-01
We study the robustness of networks under node removal, considering random node failure, as well as targeted node attacks based on network centrality measures. Whilst both of these have been studied in the literature, existing approaches tend to study random failure in terms of average-case
Heidema, A Geert; Thissen, Uwe; Boer, Jolanda M A; Bouwman, Freek G; Feskens, Edith J M; Mariman, Edwin C M
2009-06-01
In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch monitoring project for cardiovascular disease risk factors, men who died of CHD between initial participation (1987-1991) and end of follow-up (January 1, 2000) (N = 44) and matched controls (N = 44) were selected. Baseline plasma concentrations of proteins were measured by a multiplex immunoassay. With the use of PLS, we identified 15 proteins with prognostic value for CHD mortality and sets of proteins associated with the intermediate end points. Subsequently, sets of proteins and intermediate end points were analyzed together by Principal Components Analysis, indicating that proteins involved in inflammation explained most of the variance, followed by proteins involved in metabolism and proteins associated with total-C. This study is one of the first in which the association of a large number of plasma proteins with CHD mortality and intermediate end points is investigated by applying multivariate statistics, providing insight in the relationships among proteins, intermediate end points and CHD mortality, and a set of proteins with prognostic value.
Robustness and structure of complex networks
Shao, Shuai
This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks
Robust Statistics and Regularization for Feature Extraction and UXO Discrimination
2011-07-01
behind our inversion routines. Throughout this report we use the dipole model (Bell (2005), Pasion (2007)) to predict observed TEM data. The...data acquired over axisymmetric targets ( Pasion , 2007). Of course, the two-dipole model may not provide a good fit to data acquired over an non...in order to characterize the distributions of TOI polarizabilities. More description of this procedure is given in Pasion et al. (2011). Figure 28
Robust cluster analysis and variable selection
Ritter, Gunter
2014-01-01
Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of bot
Robust median estimator in logisitc regression
Czech Academy of Sciences Publication Activity Database
Hobza, T.; Pardo, L.; Vajda, Igor
2008-01-01
Roč. 138, č. 12 (2008), s. 3822-3840 ISSN 0378-3758 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MPO FI - IM3/136; GA MŠk(CZ) MTM 2006-06872 Institutional research plan: CEZ:AV0Z10750506 Keywords : Logistic regression * Median * Robustness * Consistency and asymptotic normality * Morgenthaler * Bianco and Yohai * Croux and Hasellbroeck Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.679, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/vajda-robust%20median%20estimator%20in%20logistic%20regression.pdf
... this page: https://medlineplus.gov/usestatistics.html MedlinePlus Statistics To use the sharing features on this page, ... By Quarter View image full size Quarterly User Statistics Quarter Page Views Unique Visitors Oct-Dec-98 ...
Robust Methods for Image Processing in Anthropology and Biomedicine
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
-, č. 86 (2011), s. 53-53 ISSN 0926-4981 Institutional research plan: CEZ:AV0Z10300504 Keywords : image analysis * robust estimation * forensic anthropology Subject RIV: BB - Applied Statistics, Operational Research
Robust Optimization in Simulation : Taguchi and Response Surface Methodology
Dellino, G.; Kleijnen, J.P.C.; Meloni, C.
2008-01-01
Optimization of simulated systems is tackled by many methods, but most methods assume known environments. This article, however, develops a 'robust' methodology for uncertain environments. This methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by
Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus
2011-01-01
In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.
Whole Frog Project and Virtual Frog Dissection Statistics wwwstats output for January 1 through duplicate or extraneous accesses. For example, in these statistics, while a POST requesting an image is as well. Note that this under-represents the bytes requested. Starting date for following statistics
Container Materials, Fabrication And Robustness
International Nuclear Information System (INIS)
Dunn, K.; Louthan, M.; Rawls, G.; Sindelar, R.; Zapp, P.; Mcclard, J.
2009-01-01
The multi-barrier 3013 container used to package plutonium-bearing materials is robust and thereby highly resistant to identified degradation modes that might cause failure. The only viable degradation mechanisms identified by a panel of technical experts were pressurization within and corrosion of the containers. Evaluations of the container materials and the fabrication processes and resulting residual stresses suggest that the multi-layered containers will mitigate the potential for degradation of the outer container and prevent the release of the container contents to the environment. Additionally, the ongoing surveillance programs and laboratory studies should detect any incipient degradation of containers in the 3013 storage inventory before an outer container is compromised.
Automatically identifying scatter in fluorescence data using robust techniques
DEFF Research Database (Denmark)
Engelen, S.; Frosch, Stina; Hubert, M.
2007-01-01
as input data for three different PARAFAC methods. Firstly inserting missing values in the scatter regions are tested, secondly an interpolation of the scatter regions is performed and finally the scatter regions are down-weighted. These results show that the PARAFAC method to choose after scatter...
Eggenberg, Niklaus; Salani, Matteo; Bierlaire, Michel
2010-01-01
Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incurred by possible modifications of the original plan to be performed when reality does not reflect what was expected in the planning phase. The modern research trend focuses on "robustness" of solutions instead of yield or profit. Although ro...
Design principles for robust oscillatory behavior.
Castillo-Hair, Sebastian M; Villota, Elizabeth R; Coronado, Alberto M
2015-09-01
Oscillatory responses are ubiquitous in regulatory networks of living organisms, a fact that has led to extensive efforts to study and replicate the circuits involved. However, to date, design principles that underlie the robustness of natural oscillators are not completely known. Here we study a three-component enzymatic network model in order to determine the topological requirements for robust oscillation. First, by simulating every possible topological arrangement and varying their parameter values, we demonstrate that robust oscillators can be obtained by augmenting the number of both negative feedback loops and positive autoregulations while maintaining an appropriate balance of positive and negative interactions. We then identify network motifs, whose presence in more complex topologies is a necessary condition for obtaining oscillatory responses. Finally, we pinpoint a series of simple architectural patterns that progressively render more robust oscillators. Together, these findings can help in the design of more reliable synthetic biomolecular networks and may also have implications in the understanding of other oscillatory systems.
Chang, Huijuan; Gao, Qiuying; Ding, Wei; Qing, Xueqin
2018-01-01
Acute myeloid leukemia (AML) is a heterogeneous disease, and survival signatures are urgently needed to better monitor treatment. MiRNAs displayed vital regulatory roles on target genes, which was necessary involved in the complex disease. We therefore examined the expression levels of miRNAs and genes to identify robust signatures for survival benefit analyses. First, we reconstructed subpathway graphs by embedding miRNA components that were derived from low-throughput miRNA-gene interactions. Then, we randomly divided the data sets from The Cancer Genome Atlas (TCGA) into training and testing sets, and further formed 100 subsets based on the training set. Using each subset, we identified survival-related miRNAs and genes, and identified survival subpathways based on the reconstructed subpathway graphs. After statistical analyses of these survival subpathways, the most robust subpathways with the top three ranks were identified, and risk scores were calculated based on these robust subpathways for AML patient prognoses. Among these robust subpathways, three representative subpathways, path: 05200_10 from Pathways in cancer, path: 04110_20 from Cell cycle, and path: 04510_8 from Focal adhesion, were significantly associated with patient survival in the TCGA training and testing sets based on subpathway risk scores. In conclusion, we performed integrated analyses of miRNAs and genes to identify robust prognostic subpathways, and calculated subpathway risk scores to characterize AML patient survival.
van Uitert, Miranda; Moerland, Perry D.; Enquobahrie, Daniel A.; Laivuori, Hannele; van der Post, Joris A. M.; Ris-Stalpers, Carrie; Afink, Gijs B.
2015-01-01
Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia
Whitney, Heather M.; Drukker, Karen; Edwards, Alexandra; Papaioannou, John; Giger, Maryellen L.
2018-02-01
Radiomics features extracted from breast lesion images have shown potential in diagnosis and prognosis of breast cancer. As clinical institutions transition from 1.5 T to 3.0 T magnetic resonance imaging (MRI), it is helpful to identify robust features across these field strengths. In this study, dynamic contrast-enhanced MR images were acquired retrospectively under IRB/HIPAA compliance, yielding 738 cases: 241 and 124 benign lesions imaged at 1.5 T and 3.0 T and 231 and 142 luminal A cancers imaged at 1.5 T and 3.0 T, respectively. Lesions were segmented using a fuzzy C-means method. Extracted radiomic values for each group of lesions by cancer status and field strength of acquisition were compared using a Kolmogorov-Smirnov test for the null hypothesis that two groups being compared came from the same distribution, with p-values being corrected for multiple comparisons by the Holm-Bonferroni method. Two shape features, one texture feature, and three enhancement variance kinetics features were found to be potentially robust. All potentially robust features had areas under the receiver operating characteristic curve (AUC) statistically greater than 0.5 in the task of distinguishing between lesion types (range of means 0.57-0.78). The significant difference in voxel size between field strength of acquisition limits the ability to affirm more features as robust or not robust according to field strength alone, and inhomogeneities in static field strength and radiofrequency field could also have affected the assessment of kinetic curve features as robust or not. Vendor-specific image scaling could have also been a factor. These findings will contribute to the development of radiomic signatures that use features identified as robust across field strength.
Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping
2016-01-01
To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...
The Variation Management Framework (VMF) for Robust Design
DEFF Research Database (Denmark)
Howard, Thomas J.; Ebro, Martin; Eifler, Tobias
2014-01-01
Robust Design is an approach to reduce the effects of variation. There are numerous tools,methods and models associated with robust design, however, there is both a lack of a processmodel formalising the step of a robust design process and a framework tying the models together.In this paper we pr...... in the market place and identifies areaswhere action can be taken against variation. An additional benefit of the framework is that itmakes the link between visual/sensory/perceptual robustness, product robustness, and productionvariation (Six Sigma)....
Sadovskii, Michael V
2012-01-01
This volume provides a compact presentation of modern statistical physics at an advanced level. Beginning with questions on the foundations of statistical mechanics all important aspects of statistical physics are included, such as applications to ideal gases, the theory of quantum liquids and superconductivity and the modern theory of critical phenomena. Beyond that attention is given to new approaches, such as quantum field theory methods and non-equilibrium problems.
Handling Occlusions for Robust Augmented Reality Systems
Directory of Open Access Journals (Sweden)
Maidi Madjid
2010-01-01
Full Text Available Abstract In Augmented Reality applications, the human perception is enhanced with computer-generated graphics. These graphics must be exactly registered to real objects in the scene and this requires an effective Augmented Reality system to track the user's viewpoint. In this paper, a robust tracking algorithm based on coded fiducials is presented. Square targets are identified and pose parameters are computed using a hybrid approach based on a direct method combined with the Kalman filter. An important factor for providing a robust Augmented Reality system is the correct handling of targets occlusions by real scene elements. To overcome tracking failure due to occlusions, we extend our method using an optical flow approach to track visible points and maintain virtual graphics overlaying when targets are not identified. Our proposed real-time algorithm is tested with different camera viewpoints under various image conditions and shows to be accurate and robust.
Goodman, Joseph W
2015-01-01
This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications. The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced i
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il
2017-05-15
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their ‘public relations’ for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford’s law, and 1/f noise. - Highlights: • Harmonic statistics are described and reviewed in detail. • Connections to various statistical laws are established. • Connections to perturbation, renormalization and dynamics are established.
Szulc, Stefan
1965-01-01
Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then
... Testing Treatment & Outcomes Health Professionals Statistics More Resources Candidiasis Candida infections of the mouth, throat, and esophagus Vaginal candidiasis Invasive candidiasis Definition Symptoms Risk & Prevention Sources Diagnosis ...
Heteroscedasticity resistant robust covariance matrix estimator
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2010-01-01
Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf
Robust efficient video fingerprinting
Puri, Manika; Lubin, Jeffrey
2009-02-01
We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.
Petocz, Peter; Sowey, Eric
2012-01-01
The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…
Petocz, Peter; Sowey, Eric
2008-01-01
In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…
Glaz, Joseph
2009-01-01
Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
Lyons, L.
2016-01-01
Accelerators and detectors are expensive, both in terms of money and human effort. It is thus important to invest effort in performing a good statistical anal- ysis of the data, in order to extract the best information from it. This series of five lectures deals with practical aspects of statistical issues that arise in typical High Energy Physics analyses.
Energy Technology Data Exchange (ETDEWEB)
Re, V., E-mail: re@unive.it [Department of Molecular Sciences and Nanosystems, Ca’ Foscari University of Venice, Calle Larga Santa Marta 2137, Dorsoduro, 40123 Venice (Italy); National Engineering School of Sfax (ENIS) - Laboratory of Radio-Analysis and Environment (LRAE) Sfax (Tunisia); Sacchi, E. [Department of Earth and Environmental Sciences, University of Pavia, Via Ferrata 1, 27100 Pavia (Italy); Mas-Pla, J. [Grup de Geologia Aplicada i Ambiental (GAIA), Centre de Geologia i Cartografia Ambientals (GEOCAMB), Department of Environmental Sciences, University of Girona, 17071 Girona (Spain); Catalan Institute for Water Research (ICRA), 17003 Girona (Spain); Menció, A. [Grup de Geologia Aplicada i Ambiental (GAIA), Centre de Geologia i Cartografia Ambientals (GEOCAMB), Department of Environmental Sciences, University of Girona, 17071 Girona (Spain); El Amrani, N. [Faculty of Sciences and techniques, University Hassan 1er, Settat (Morocco)
2014-12-01
) from the Selouane River is responsible for the high groundwater salinity whilst Mixing Processes (MIX) occur in absence of irrigation activities. - Highlights: • Effects of irrigation and seasonality on groundwater quality are evaluated. • GW isotopic composition clearly identifies recharge sources and irrigation impact • 3 PCA varifactors extracted: salinization, soil biological activity and nitrate pollution • The aquifer shows high vulnerability, but good resilience to agricultural inputs • Hydrogeochemistry and statistics as tools for coastal aquifer management.
International Nuclear Information System (INIS)
Re, V.; Sacchi, E.; Mas-Pla, J.; Menció, A.; El Amrani, N.
2014-01-01
) from the Selouane River is responsible for the high groundwater salinity whilst Mixing Processes (MIX) occur in absence of irrigation activities. - Highlights: • Effects of irrigation and seasonality on groundwater quality are evaluated. • GW isotopic composition clearly identifies recharge sources and irrigation impact • 3 PCA varifactors extracted: salinization, soil biological activity and nitrate pollution • The aquifer shows high vulnerability, but good resilience to agricultural inputs • Hydrogeochemistry and statistics as tools for coastal aquifer management
Nick, Todd G
2007-01-01
Statistics is defined by the Medical Subject Headings (MeSH) thesaurus as the science and art of collecting, summarizing, and analyzing data that are subject to random variation. The two broad categories of summarizing and analyzing data are referred to as descriptive and inferential statistics. This chapter considers the science and art of summarizing data where descriptive statistics and graphics are used to display data. In this chapter, we discuss the fundamentals of descriptive statistics, including describing qualitative and quantitative variables. For describing quantitative variables, measures of location and spread, for example the standard deviation, are presented along with graphical presentations. We also discuss distributions of statistics, for example the variance, as well as the use of transformations. The concepts in this chapter are useful for uncovering patterns within the data and for effectively presenting the results of a project.
New solutions for NPP robustness improvement
International Nuclear Information System (INIS)
Wolski, Alexander
2013-01-01
Fukushima accident has triggered a major re-assessment of robustness of nuclear stations. First round of evaluations has been Finished. Improvement areas and strategies have been identified. Implementation of upgrades has started world-wide. New solutions can provide substantial benefits
Robust Design of Sounds in Mechanical Mechanisms
DEFF Research Database (Denmark)
Boegedal Jensen, Annemette; Munch, Natasja; Howard, Thomas J.
2015-01-01
mechanism consisting of a toothed rack and a click arm. First several geometries of the teeth and the click arm’s head were investigated to identify the most robust and repeatable design. It was found that a flat surface in the valleys between the teeth is very beneficial in relation to repeatability...
Interrogating the topological robustness of gene regulatory circuits by randomization.
Directory of Open Access Journals (Sweden)
Bin Huang
2017-03-01
Full Text Available One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE, for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT, from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.
Robust automated knowledge capture.
Energy Technology Data Exchange (ETDEWEB)
Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt
2011-10-01
This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.
Passion, Robustness and Perseverance
DEFF Research Database (Denmark)
Lim, Miguel Antonio; Lund, Rebecca
2016-01-01
Evaluation and merit in the measured university are increasingly based on taken-for-granted assumptions about the “ideal academic”. We suggest that the scholar now needs to show that she is passionate about her work and that she gains pleasure from pursuing her craft. We suggest that passion...... and pleasure achieve an exalted status as something compulsory. The scholar ought to feel passionate about her work and signal that she takes pleasure also in the difficult moments. Passion has become a signal of robustness and perseverance in a job market characterised by funding shortages, increased pressure...... way to demonstrate their potential and, crucially, their passion for their work. Drawing on the literature on technologies of governance, we reflect on what is captured and what is left out by these two evaluation instruments. We suggest that bibliometric analysis at the individual level is deeply...
Robust Optical Flow Estimation
Directory of Open Access Journals (Sweden)
Javier Sánchez Pérez
2013-10-01
Full Text Available n this work, we describe an implementation of the variational method proposed by Brox etal. in 2004, which yields accurate optical flows with low running times. It has several benefitswith respect to the method of Horn and Schunck: it is more robust to the presence of outliers,produces piecewise-smooth flow fields and can cope with constant brightness changes. Thismethod relies on the brightness and gradient constancy assumptions, using the information ofthe image intensities and the image gradients to find correspondences. It also generalizes theuse of continuous L1 functionals, which help mitigate the effect of outliers and create a TotalVariation (TV regularization. Additionally, it introduces a simple temporal regularizationscheme that enforces a continuous temporal coherence of the flow fields.
Robust Multimodal Dictionary Learning
Cao, Tian; Jojic, Vladimir; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc
2014-01-01
We propose a robust multimodal dictionary learning method for multimodal images. Joint dictionary learning for both modalities may be impaired by lack of correspondence between image modalities in training data, for example due to areas of low quality in one of the modalities. Dictionaries learned with such non-corresponding data will induce uncertainty about image representation. In this paper, we propose a probabilistic model that accounts for image areas that are poorly corresponding between the image modalities. We cast the problem of learning a dictionary in presence of problematic image patches as a likelihood maximization problem and solve it with a variant of the EM algorithm. Our algorithm iterates identification of poorly corresponding patches and re-finements of the dictionary. We tested our method on synthetic and real data. We show improvements in image prediction quality and alignment accuracy when using the method for multimodal image registration. PMID:24505674
Robust snapshot interferometric spectropolarimetry.
Kim, Daesuk; Seo, Yoonho; Yoon, Yonghee; Dembele, Vamara; Yoon, Jae Woong; Lee, Kyu Jin; Magnusson, Robert
2016-05-15
This Letter describes a Stokes vector measurement method based on a snapshot interferometric common-path spectropolarimeter. The proposed scheme, which employs an interferometric polarization-modulation module, can extract the spectral polarimetric parameters Ψ(k) and Δ(k) of a transmissive anisotropic object by which an accurate Stokes vector can be calculated in the spectral domain. It is inherently strongly robust to the object 3D pose variation, since it is designed distinctly so that the measured object can be placed outside of the interferometric module. Experiments are conducted to verify the feasibility of the proposed system. The proposed snapshot scheme enables us to extract the spectral Stokes vector of a transmissive anisotropic object within tens of msec with high accuracy.
Improving Electronic Sensor Reliability by Robust Outlier Screening
Directory of Open Access Journals (Sweden)
Federico Cuesta
2013-10-01
Full Text Available Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs. This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB and Bad Bin in a Bad Cluster (BBBC and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT, as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.
Blakemore, J S
1962-01-01
Semiconductor Statistics presents statistics aimed at complementing existing books on the relationships between carrier densities and transport effects. The book is divided into two parts. Part I provides introductory material on the electron theory of solids, and then discusses carrier statistics for semiconductors in thermal equilibrium. Of course a solid cannot be in true thermodynamic equilibrium if any electrical current is passed; but when currents are reasonably small the distribution function is but little perturbed, and the carrier distribution for such a """"quasi-equilibrium"""" co
Wannier, Gregory Hugh
1966-01-01
Until recently, the field of statistical physics was traditionally taught as three separate subjects: thermodynamics, statistical mechanics, and kinetic theory. This text, a forerunner in its field and now a classic, was the first to recognize the outdated reasons for their separation and to combine the essentials of the three subjects into one unified presentation of thermal physics. It has been widely adopted in graduate and advanced undergraduate courses, and is recommended throughout the field as an indispensable aid to the independent study and research of statistical physics.Designed for
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Robust Instrumentation[Water treatment for power plant]; Robust Instrumentering
Energy Technology Data Exchange (ETDEWEB)
Wik, Anders [Vattenfall Utveckling AB, Stockholm (Sweden)
2003-08-01
Cementa Slite Power Station is a heat recovery steam generator (HRSG) with moderate steam data; 3.0 MPa and 420 deg C. The heat is recovered from Cementa, a cement industry, without any usage of auxiliary fuel. The Power station commenced operation in 2001. The layout of the plant is unusual, there are no similar in Sweden and very few world-wide, so the operational experiences are limited. In connection with the commissioning of the power plant a R and D project was identified with the objective to minimise the manpower needed for chemistry management of the plant. The lean chemistry management is based on robust instrumentation and chemical-free water treatment plant. The concept with robust instrumentation consists of the following components; choice of on-line instrumentation with a minimum of O and M and a chemical-free water treatment. The parameters are specific conductivity, cation conductivity, oxygen and pH. In addition to that, two fairly new on-line instruments were included; corrosion monitors and differential pH calculated from specific and cation conductivity. The chemical-free water treatment plant consists of softening, reverse osmosis and electro-deionisation. The operational experience shows that the cycle chemistry is not within the guidelines due to major problems with the operation of the power plant. These problems have made it impossible to reach steady state and thereby not viable to fully verify and validate the concept with robust instrumentation. From readings on the panel of the online analysers some conclusions may be drawn, e.g. the differential pH measurements have fulfilled the expectations. The other on-line analysers have been working satisfactorily apart from contamination with turbine oil, which has been noticed at least twice. The corrosion monitors seem to be working but the lack of trend curves from the mainframe computer system makes it hard to draw any clear conclusions. The chemical-free water treatment has met all
Robustness Analyses of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Hald, Frederik
2013-01-01
The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many mo...... with respect to robustness of timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......The robustness of structural systems has obtained a renewed interest arising from a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures, many...... modern building codes consider the need for the robustness of structures and provide strategies and methods to obtain robustness. Therefore, a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues...
Understanding advanced statistical methods
Westfall, Peter
2013-01-01
Introduction: Probability, Statistics, and ScienceReality, Nature, Science, and ModelsStatistical Processes: Nature, Design and Measurement, and DataModelsDeterministic ModelsVariabilityParametersPurely Probabilistic Statistical ModelsStatistical Models with Both Deterministic and Probabilistic ComponentsStatistical InferenceGood and Bad ModelsUses of Probability ModelsRandom Variables and Their Probability DistributionsIntroductionTypes of Random Variables: Nominal, Ordinal, and ContinuousDiscrete Probability Distribution FunctionsContinuous Probability Distribution FunctionsSome Calculus-Derivatives and Least SquaresMore Calculus-Integrals and Cumulative Distribution FunctionsProbability Calculation and SimulationIntroductionAnalytic Calculations, Discrete and Continuous CasesSimulation-Based ApproximationGenerating Random NumbersIdentifying DistributionsIntroductionIdentifying Distributions from Theory AloneUsing Data: Estimating Distributions via the HistogramQuantiles: Theoretical and Data-Based Estimate...
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
U.S. Department of Health & Human Services — The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health...
Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Data about the usage of the WPRDC site and its various datasets, obtained by combining Google Analytics statistics with information from the WPRDC's data portal.
Serdobolskii, Vadim Ivanovich
2007-01-01
This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...
... Search Form Controls Cancel Submit Search the CDC Gonorrhea Note: Javascript is disabled or is not supported ... Twitter STD on Facebook Sexually Transmitted Diseases (STDs) Gonorrhea Statistics Recommend on Facebook Tweet Share Compartir Gonorrhea ...
DEFF Research Database (Denmark)
Tryggestad, Kjell
2004-01-01
The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit...... in different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved...
Dynamics robustness of cascading systems.
Directory of Open Access Journals (Sweden)
Jonathan T Young
2017-03-01
Full Text Available A most important property of biochemical systems is robustness. Static robustness, e.g., homeostasis, is the insensitivity of a state against perturbations, whereas dynamics robustness, e.g., homeorhesis, is the insensitivity of a dynamic process. In contrast to the extensively studied static robustness, dynamics robustness, i.e., how a system creates an invariant temporal profile against perturbations, is little explored despite transient dynamics being crucial for cellular fates and are reported to be robust experimentally. For example, the duration of a stimulus elicits different phenotypic responses, and signaling networks process and encode temporal information. Hence, robustness in time courses will be necessary for functional biochemical networks. Based on dynamical systems theory, we uncovered a general mechanism to achieve dynamics robustness. Using a three-stage linear signaling cascade as an example, we found that the temporal profiles and response duration post-stimulus is robust to perturbations against certain parameters. Then analyzing the linearized model, we elucidated the criteria of when signaling cascades will display dynamics robustness. We found that changes in the upstream modules are masked in the cascade, and that the response duration is mainly controlled by the rate-limiting module and organization of the cascade's kinetics. Specifically, we found two necessary conditions for dynamics robustness in signaling cascades: 1 Constraint on the rate-limiting process: The phosphatase activity in the perturbed module is not the slowest. 2 Constraints on the initial conditions: The kinase activity needs to be fast enough such that each module is saturated even with fast phosphatase activity and upstream changes are attenuated. We discussed the relevance of such robustness to several biological examples and the validity of the above conditions therein. Given the applicability of dynamics robustness to a variety of systems, it
Robust inference in sample selection models
Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio
2015-01-01
The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.
Robust inference in sample selection models
Zhelonkin, Mikhail
2015-11-20
The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.
Robust power spectral estimation for EEG data.
Melman, Tamar; Victor, Jonathan D
2016-08-01
Typical electroencephalogram (EEG) recordings often contain substantial artifact. These artifacts, often large and intermittent, can interfere with quantification of the EEG via its power spectrum. To reduce the impact of artifact, EEG records are typically cleaned by a preprocessing stage that removes individual segments or components of the recording. However, such preprocessing can introduce bias, discard available signal, and be labor-intensive. With this motivation, we present a method that uses robust statistics to reduce dependence on preprocessing by minimizing the effect of large intermittent outliers on the spectral estimates. Using the multitaper method (Thomson, 1982) as a starting point, we replaced the final step of the standard power spectrum calculation with a quantile-based estimator, and the Jackknife approach to confidence intervals with a Bayesian approach. The method is implemented in provided MATLAB modules, which extend the widely used Chronux toolbox. Using both simulated and human data, we show that in the presence of large intermittent outliers, the robust method produces improved estimates of the power spectrum, and that the Bayesian confidence intervals yield close-to-veridical coverage factors. The robust method, as compared to the standard method, is less affected by artifact: inclusion of outliers produces fewer changes in the shape of the power spectrum as well as in the coverage factor. In the presence of large intermittent outliers, the robust method can reduce dependence on data preprocessing as compared to standard methods of spectral estimation. Copyright © 2016 Elsevier B.V. All rights reserved.
Emergence of robustness in networks of networks
Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.
2017-06-01
A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.
On the Robustness of Poverty Predictors
DEFF Research Database (Denmark)
Arndt, Channing; Nhate, Virgulino; Silva, Patricia Castro Da
Monitoring of poverty requires timely household budget data. However, such data are not available as frequently as needed for policy purposes. Recently, statistical methods have emerged to predict poverty overtime by combining detailed household consumption and expenditure data with more frequent...... data collected from other surveys. In this paper we compare poverty predictions for Mozambique using different source data to test the robustness of the predicted poverty statistics. A critical element in this exercise of predicting poverty overtime is the stability of the parameters that determine...... household consumption. We find that the assumption of stable consumption determinants does not hold for Mozambique during the time period examined. We also examine what drives the resulting predicted poverty statistics. The paper then considers the policy implications of these findings for Mozambique...
Goodman, J. W.
This book is based on the thesis that some training in the area of statistical optics should be included as a standard part of any advanced optics curriculum. Random variables are discussed, taking into account definitions of probability and random variables, distribution functions and density functions, an extension to two or more random variables, statistical averages, transformations of random variables, sums of real random variables, Gaussian random variables, complex-valued random variables, and random phasor sums. Other subjects examined are related to random processes, some first-order properties of light waves, the coherence of optical waves, some problems involving high-order coherence, effects of partial coherence on imaging systems, imaging in the presence of randomly inhomogeneous media, and fundamental limits in photoelectric detection of light. Attention is given to deterministic versus statistical phenomena and models, the Fourier transform, and the fourth-order moment of the spectrum of a detected speckle image.
Schwabl, Franz
2006-01-01
The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...
Jana, Madhusudan
2015-01-01
Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...
Guénault, Tony
2007-01-01
In this revised and enlarged second edition of an established text Tony Guénault provides a clear and refreshingly readable introduction to statistical physics, an essential component of any first degree in physics. The treatment itself is self-contained and concentrates on an understanding of the physical ideas, without requiring a high level of mathematical sophistication. A straightforward quantum approach to statistical averaging is adopted from the outset (easier, the author believes, than the classical approach). The initial part of the book is geared towards explaining the equilibrium properties of a simple isolated assembly of particles. Thus, several important topics, for example an ideal spin-½ solid, can be discussed at an early stage. The treatment of gases gives full coverage to Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein statistics. Towards the end of the book the student is introduced to a wider viewpoint and new chapters are included on chemical thermodynamics, interactions in, for exam...
Robust Trust in Expert Testimony
Directory of Open Access Journals (Sweden)
Christian Dahlman
2015-05-01
Full Text Available The standard of proof in criminal trials should require that the evidence presented by the prosecution is robust. This requirement of robustness says that it must be unlikely that additional information would change the probability that the defendant is guilty. Robustness is difficult for a judge to estimate, as it requires the judge to assess the possible effect of information that the he or she does not have. This article is concerned with expert witnesses and proposes a method for reviewing the robustness of expert testimony. According to the proposed method, the robustness of expert testimony is estimated with regard to competence, motivation, external strength, internal strength and relevance. The danger of trusting non-robust expert testimony is illustrated with an analysis of the Thomas Quick Case, a Swedish legal scandal where a patient at a mental institution was wrongfully convicted for eight murders.
Mandl, Franz
1988-01-01
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scient
Rohatgi, Vijay K
2003-01-01
Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth
Levine-Wissing, Robin
2012-01-01
All Access for the AP® Statistics Exam Book + Web + Mobile Everything you need to prepare for the Advanced Placement® exam, in a study system built around you! There are many different ways to prepare for an Advanced Placement® exam. What's best for you depends on how much time you have to study and how comfortable you are with the subject matter. To score your highest, you need a system that can be customized to fit you: your schedule, your learning style, and your current level of knowledge. This book, and the online tools that come with it, will help you personalize your AP® Statistics prep
Davidson, Norman
2003-01-01
Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody
Indian Academy of Sciences (India)
inference and finite population sampling. Sudhakar Kunte. Elements of statistical computing are discussed in this series. ... which captain gets an option to decide whether to field first or bat first ... may of course not be fair, in the sense that the team which wins ... describe two methods of drawing a random number between 0.
Schrödinger, Erwin
1952-01-01
Nobel Laureate's brilliant attempt to develop a simple, unified standard method of dealing with all cases of statistical thermodynamics - classical, quantum, Bose-Einstein, Fermi-Dirac, and more.The work also includes discussions of Nernst theorem, Planck's oscillator, fluctuations, the n-particle problem, problem of radiation, much more.
Robust structural optimization using Gauss-type quadrature formula
International Nuclear Information System (INIS)
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei
2009-01-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust structural optimization using Gauss-type quadrature formula
Energy Technology Data Exchange (ETDEWEB)
Lee, Sang Hoon; Seo, Ki Seog [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Chen, Shikui; Chen, Wei [Northwestern University, Illinois (United States)
2009-07-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the Tensor Product Quadrature (TPQ) formula and the Univariate Dimension Reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust Structural Optimization Using Gauss-type Quadrature Formula
Energy Technology Data Exchange (ETDEWEB)
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2009-08-15
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty.
Robust Structural Optimization Using Gauss-type Quadrature Formula
International Nuclear Information System (INIS)
Lee, Sang Hoon; Seo, Ki Seog; Chen, Shikui; Chen, Wei
2009-01-01
In robust design, the mean and variance of design performance are frequently used to measure the design performance and its robustness under uncertainties. In this paper, we present the Gauss-type quadrature formula as a rigorous method for mean and variance estimation involving arbitrary input distributions and further extend its use to robust design optimization. One dimensional Gauss-type quadrature formula are constructed from the input probability distributions and utilized in the construction of multidimensional quadrature formula such as the tensor product quadrature (TPQ) formula and the univariate dimension reduction (UDR) method. To improve the efficiency of using it for robust design optimization, a semi-analytic design sensitivity analysis with respect to the statistical moments is proposed. The proposed approach is applied to a simple bench mark problems and robust topology optimization of structures considering various types of uncertainty
Optimal Robust Self-Testing by Binary Nonlocal XOR Games
Miller, Carl A.; Shi, Yaoyun
2013-01-01
Self-testing a quantum apparatus means verifying the existence of a certain quantum state as well as the effect of the associated measuring devices based only on the statistics of the measurement outcomes. Robust (i.e., error-tolerant) self-testing quantum apparatuses are critical building blocks for quantum cryptographic protocols that rely on imperfect or untrusted devices. We devise a general scheme for proving optimal robust self-testing properties for tests based on nonlocal binary XOR g...
Influence Function and Robust Variant of Kernel Canonical Correlation Analysis
Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping
2017-01-01
Many unsupervised kernel methods rely on the estimation of the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). Both kernel CO and kernel CCO are sensitive to contaminated data, even when bounded positive definite kernels are used. To the best of our knowledge, there are few well-founded robust kernel methods for statistical unsupervised learning. In addition, while the influence function (IF) of an estimator can characterize its robustness, asymptotic ...
Robust boosting via convex optimization
Rätsch, Gunnar
2001-12-01
In this work we consider statistical learning problems. A learning machine aims to extract information from a set of training examples such that it is able to predict the associated label on unseen examples. We consider the case where the resulting classification or regression rule is a combination of simple rules - also called base hypotheses. The so-called boosting algorithms iteratively find a weighted linear combination of base hypotheses that predict well on unseen data. We address the following issues: o The statistical learning theory framework for analyzing boosting methods. We study learning theoretic guarantees on the prediction performance on unseen examples. Recently, large margin classification techniques emerged as a practical result of the theory of generalization, in particular Boosting and Support Vector Machines. A large margin implies a good generalization performance. Hence, we analyze how large the margins in boosting are and find an improved algorithm that is able to generate the maximum margin solution. o How can boosting methods be related to mathematical optimization techniques? To analyze the properties of the resulting classification or regression rule, it is of high importance to understand whether and under which conditions boosting converges. We show that boosting can be used to solve large scale constrained optimization problems, whose solutions are well characterizable. To show this, we relate boosting methods to methods known from mathematical optimization, and derive convergence guarantees for a quite general family of boosting algorithms. o How to make Boosting noise robust? One of the problems of current boosting techniques is that they are sensitive to noise in the training sample. In order to make boosting robust, we transfer the soft margin idea from support vector learning to boosting. We develop theoretically motivated regularized algorithms that exhibit a high noise robustness. o How to adapt boosting to regression problems
Heavy-tailed distributions and robustness in economics and finance
Ibragimov, Marat; Walden, Johan
2015-01-01
This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailedness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently developed robust inference approaches are discussed and illustrated, together with applications.
Robust and distributed hypothesis testing
Gül, Gökhan
2017-01-01
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...
Robustness of IPTV business models
Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.
2008-01-01
The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we
Robustness Evaluation of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard
2009-01-01
Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....
International Nuclear Information System (INIS)
Anon.
1994-01-01
For the years 1992 and 1993, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period. The tables and figures shown in this publication are: Changes in the volume of GNP and energy consumption; Coal consumption; Natural gas consumption; Peat consumption; Domestic oil deliveries; Import prices of oil; Price development of principal oil products; Fuel prices for power production; Total energy consumption by source; Electricity supply; Energy imports by country of origin in 1993; Energy exports by recipient country in 1993; Consumer prices of liquid fuels; Consumer prices of hard coal and natural gas, prices of indigenous fuels; Average electricity price by type of consumer; Price of district heating by type of consumer and Excise taxes and turnover taxes included in consumer prices of some energy sources
Geert Heidema, A.; Thissen, U.; Boer, J.M.A.; Bouwman, F.G.; Feskens, E.J.M.; Mariman, E.C.M.
2009-01-01
In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch
Goodman, Joseph W.
2000-07-01
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research
Natrella, Mary Gibbons
1963-01-01
Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations
Understanding Statistics and Statistics Education: A Chinese Perspective
Shi, Ning-Zhong; He, Xuming; Tao, Jian
2009-01-01
In recent years, statistics education in China has made great strides. However, there still exists a fairly large gap with the advanced levels of statistics education in more developed countries. In this paper, we identify some existing problems in statistics education in Chinese schools and make some proposals as to how they may be overcome. We…
Identifiability in stochastic models
1992-01-01
The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Official Statistics and Statistics Education: Bridging the Gap
Directory of Open Access Journals (Sweden)
Gal Iddo
2017-03-01
Full Text Available This article aims to challenge official statistics providers and statistics educators to ponder on how to help non-specialist adult users of statistics develop those aspects of statistical literacy that pertain to official statistics. We first document the gap in the literature in terms of the conceptual basis and educational materials needed for such an undertaking. We then review skills and competencies that may help adults to make sense of statistical information in areas of importance to society. Based on this review, we identify six elements related to official statistics about which non-specialist adult users should possess knowledge in order to be considered literate in official statistics: (1 the system of official statistics and its work principles; (2 the nature of statistics about society; (3 indicators; (4 statistical techniques and big ideas; (5 research methods and data sources; and (6 awareness and skills for citizens’ access to statistical reports. Based on this ad hoc typology, we discuss directions that official statistics providers, in cooperation with statistics educators, could take in order to (1 advance the conceptualization of skills needed to understand official statistics, and (2 expand educational activities and services, specifically by developing a collaborative digital textbook and a modular online course, to improve public capacity for understanding of official statistics.
Application of Statistics in Engineering Technology Programs
Zhan, Wei; Fink, Rainer; Fang, Alex
2010-01-01
Statistics is a critical tool for robustness analysis, measurement system error analysis, test data analysis, probabilistic risk assessment, and many other fields in the engineering world. Traditionally, however, statistics is not extensively used in undergraduate engineering technology (ET) programs, resulting in a major disconnect from industry…
International Nuclear Information System (INIS)
Anon.
1989-01-01
World data from the United Nation's latest Energy Statistics Yearbook, first published in our last issue, are completed here. The 1984-86 data were revised and 1987 data added for world commercial energy production and consumption, world natural gas plant liquids production, world LP-gas production, imports, exports, and consumption, world residual fuel oil production, imports, exports, and consumption, world lignite production, imports, exports, and consumption, world peat production and consumption, world electricity production, imports, exports, and consumption (Table 80), and world nuclear electric power production
A robust nonlinear filter for image restoration.
Koivunen, V
1995-01-01
A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.
Theoretical Framework for Robustness Evaluation
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2011-01-01
This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...
Robustness of airline route networks
Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David
2016-03-01
Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.
Robust Wave Resource Estimation
DEFF Research Database (Denmark)
Lavelle, John; Kofoed, Jens Peter
2013-01-01
density estimates of the PDF as a function both of Hm0 and Tp, and Hm0 and T0;2, together with the mean wave power per unit crest length, Pw, as a function of Hm0 and T0;2. The wave elevation parameters, from which the wave parameters are calculated, are filtered to correct or remove spurious data....... An overview is given of the methods used to do this, and a method for identifying outliers of the wave elevation data, based on the joint distribution of wave elevations and accelerations, is presented. The limitations of using a JONSWAP spectrum to model the measured wave spectra as a function of Hm0 and T0......;2 or Hm0 and Tp for the Hanstholm site data are demonstrated. As an alternative, the non-parametric loess method, which does not rely on any assumptions about the shape of the wave elevation spectra, is used to accurately estimate Pw as a function of Hm0 and T0;2....
Robust Portfolio Optimization Using Pseudodistances.
Toma, Aida; Leoni-Aubin, Samuela
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature.
Robustizing Circuit Optimization using Huber Functions
DEFF Research Database (Denmark)
Bandler, John W.; Biernacki, Radek M.; Chen, Steve H.
1993-01-01
The authors introduce a novel approach to 'robustizing' microwave circuit optimization using Huber functions, both two-sided and one-sided. They compare Huber optimization with l/sub 1/, l/sub 2/, and minimax methods in the presence of faults, large and small measurement errors, bad starting poin......, a preliminary optimization by selecting a small number of dominant variables. It is demonstrated, through multiplexer optimization, that the one-sided Huber function can be more effective and efficient than minimax in overcoming a bad starting point.......The authors introduce a novel approach to 'robustizing' microwave circuit optimization using Huber functions, both two-sided and one-sided. They compare Huber optimization with l/sub 1/, l/sub 2/, and minimax methods in the presence of faults, large and small measurement errors, bad starting points......, and statistical uncertainties. They demonstrate FET statistical modeling, multiplexer optimization, analog fault location, and data fitting. They extend the Huber concept by introducing a 'one-sided' Huber function for large-scale optimization. For large-scale problems, the designer often attempts, by intuition...
Robust methods for data reduction
Farcomeni, Alessio
2015-01-01
Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy
Robust Design Impact Metrics: Measuring the effect of implementing and using Robust Design
DEFF Research Database (Denmark)
Ebro, Martin; Olesen, Jesper; Howard, Thomas J.
2014-01-01
Measuring the performance of an organisation’s product development process can be challenging due to the limited use of metrics in R&D. An organisation considering whether to use Robust Design as an integrated part of their development process may find it difficult to define whether it is relevant......, and afterwards measure the effect of having implemented it. This publication identifies and evaluates Robust Design-related metrics and finds that 2 metrics are especially useful: 1) Relative amount of R&D Resources spent after Design Verification and 2) Number of ‘change notes’ after Design Verification....... The metrics have been applied in a case company to test the assumptions made during the evaluation. It is concluded that the metrics are useful and relevant, but further work is necessary to make a proper overview and categorisation of different types of robustness related metrics....
Joyce, Brendan; Lee, Danny; Rubio, Alex; Ogurtsov, Aleksey; Alves, Gelio; Yu, Yi-Kuo
2018-01-01
Abstract Objective RAId is a software package that has been actively developed for the past 10 years for computationally and visually analyzing MS/MS data. Founded on rigorous statistical methods, RAId’s core program computes accurate E-values for peptides and proteins identified during database searches. Making this robust tool readily accessible for the proteomics community by developing a graphical user interface (GUI) is our main goa...
High-dimensional Data in Economics and their (Robust) Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2017-01-01
Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability
National Statistical Commission and Indian Official Statistics*
Indian Academy of Sciences (India)
IAS Admin
a good collection of official statistics of that time. With more .... statistical agencies and institutions to provide details of statistical activities .... ing several training programmes. .... ful completion of Indian Statistical Service examinations, the.
The effectiveness of robust RMCD control chart as outliers’ detector
Darmanto; Astutik, Suci
2017-12-01
A well-known control chart to monitor a multivariate process is Hotelling’s T 2 which its parameters are estimated classically, very sensitive and also marred by masking and swamping of outliers data effect. To overcome these situation, robust estimators are strongly recommended. One of robust estimators is re-weighted minimum covariance determinant (RMCD) which has robust characteristics as same as MCD. In this paper, the effectiveness term is accuracy of the RMCD control chart in detecting outliers as real outliers. In other word, how effectively this control chart can identify and remove masking and swamping effects of outliers. We assessed the effectiveness the robust control chart based on simulation by considering different scenarios: n sample sizes, proportion of outliers, number of p quality characteristics. We found that in some scenarios, this RMCD robust control chart works effectively.
Sex differences in discriminative power of volleyball game-related statistics.
João, Paulo Vicente; Leite, Nuno; Mesquita, Isabel; Sampaio, Jaime
2010-12-01
To identify sex differences in volleyball game-related statistics, the game-related statistics of several World Championships in 2007 (N=132) were analyzed using the software VIS from the International Volleyball Federation. Discriminant analysis was used to identify the game-related statistics which better discriminated performances by sex. Analysis yielded an emphasis on fault serves (SC = -.40), shot spikes (SC = .40), and reception digs (SC = .31). Specific robust numbers represent that considerable variability was evident in the game-related statistics profile, as men's volleyball games were better associated with terminal actions (errors of service), and women's volleyball games were characterized by continuous actions (in defense and attack). These differences may be related to the anthropometric and physiological differences between women and men and their influence on performance profiles.
Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD
Newman, Perry A.; Putko, Michele M.; Taylor, Arthur C., III
2004-01-01
A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.
Design optimization for cost and quality: The robust design approach
Unal, Resit
1990-01-01
Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.
Bukhari, Hassan J.
2017-12-01
In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.
Robust dynamical effects in traffic and chaotic maps on trees
Indian Academy of Sciences (India)
Here we study two types of well-defined diffusive dynamics on scale-free trees: traffic of packets as navigated random walks, and chaotic standard maps coupled along the network links. We show that in both cases robust collective dynamic effects appear, which can be measured statistically and related to non-ergodicity of ...
Robust Pitch Estimation Using an Optimal Filter on Frequency Estimates
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust...
Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis
Young, Cristobal; Holsteen, Katherine
2017-01-01
Model uncertainty is pervasive in social science. A key question is how robust empirical results are to sensible changes in model specification. We present a new approach and applied statistical software for computational multimodel analysis. Our approach proceeds in two steps: First, we estimate the modeling distribution of estimates across all…
Robust Optimization in Simulation : Taguchi and Krige Combined
Dellino, G.; Kleijnen, Jack P.C.; Meloni, C.
2009-01-01
Optimization of simulated systems is the goal of many methods, but most methods as- sume known environments. We, however, develop a `robust' methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world, but replaces his statistical techniques by
Metamodel-based robust simulation-optimization : An overview
Dellino, G.; Meloni, C.; Kleijnen, J.P.C.; Dellino, Gabriella; Meloni, Carlo
2015-01-01
Optimization of simulated systems is the goal of many methods, but most methods assume known environments. We, however, develop a "robust" methodology that accounts for uncertain environments. Our methodology uses Taguchi's view of the uncertain world but replaces his statistical techniques by
Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning
DEFF Research Database (Denmark)
Chakraborty, Rudrasis; Hauberg, Søren; Vemuri, Baba C.
2017-01-01
Principal Component Analysis (PCA) is a fundamental method for estimating a linear subspace approximation to high-dimensional data. Many algorithms exist in literature to achieve a statistically robust version of PCA called RPCA. In this paper, we present a geometric framework for computing the p...
Tellinghuisen, Joel
2008-01-01
The method of least squares is probably the most powerful data analysis tool available to scientists. Toward a fuller appreciation of that power, this work begins with an elementary review of statistics fundamentals, and then progressively increases in sophistication as the coverage is extended to the theory and practice of linear and nonlinear least squares. The results are illustrated in application to data analysis problems important in the life sciences. The review of fundamentals includes the role of sampling and its connection to probability distributions, the Central Limit Theorem, and the importance of finite variance. Linear least squares are presented using matrix notation, and the significance of the key probability distributions-Gaussian, chi-square, and t-is illustrated with Monte Carlo calculations. The meaning of correlation is discussed, including its role in the propagation of error. When the data themselves are correlated, special methods are needed for the fitting, as they are also when fitting with constraints. Nonlinear fitting gives rise to nonnormal parameter distributions, but the 10% Rule of Thumb suggests that such problems will be insignificant when the parameter is sufficiently well determined. Illustrations include calibration with linear and nonlinear response functions, the dangers inherent in fitting inverted data (e.g., Lineweaver-Burk equation), an analysis of the reliability of the van't Hoff analysis, the problem of correlated data in the Guggenheim method, and the optimization of isothermal titration calorimetry procedures using the variance-covariance matrix for experiment design. The work concludes with illustrations on assessing and presenting results.
Robustness Property of Robust-BD Wald-Type Test for Varying-Dimensional General Linear Models
Directory of Open Access Journals (Sweden)
Xiao Guo
2018-03-01
Full Text Available An important issue for robust inference is to examine the stability of the asymptotic level and power of the test statistic in the presence of contaminated data. Most existing results are derived in finite-dimensional settings with some particular choices of loss functions. This paper re-examines this issue by allowing for a diverging number of parameters combined with a broader array of robust error measures, called “robust- BD ”, for the class of “general linear models”. Under regularity conditions, we derive the influence function of the robust- BD parameter estimator and demonstrate that the robust- BD Wald-type test enjoys the robustness of validity and efficiency asymptotically. Specifically, the asymptotic level of the test is stable under a small amount of contamination of the null hypothesis, whereas the asymptotic power is large enough under a contaminated distribution in a neighborhood of the contiguous alternatives, thus lending supports to the utility of the proposed robust- BD Wald-type test.
Advances in robust fractional control
Padula, Fabrizio
2015-01-01
This monograph presents design methodologies for (robust) fractional control systems. It shows the reader how to take advantage of the superior flexibility of fractional control systems compared with integer-order systems in achieving more challenging control requirements. There is a high degree of current interest in fractional systems and fractional control arising from both academia and industry and readers from both milieux are catered to in the text. Different design approaches having in common a trade-off between robustness and performance of the control system are considered explicitly. The text generalizes methodologies, techniques and theoretical results that have been successfully applied in classical (integer) control to the fractional case. The first part of Advances in Robust Fractional Control is the more industrially-oriented. It focuses on the design of fractional controllers for integer processes. In particular, it considers fractional-order proportional-integral-derivative controllers, becau...
Robustness of digital artist authentication
DEFF Research Database (Denmark)
Jacobsen, Robert; Nielsen, Morten
In many cases it is possible to determine the authenticity of a painting from digital reproductions of the paintings; this has been demonstrated for a variety of artists and with different approaches. Common to all these methods in digital artist authentication is that the potential of the method...... is in focus, while the robustness has not been considered, i.e. the degree to which the data collection process influences the decision of the method. However, in order for an authentication method to be successful in practice, it needs to be robust to plausible error sources from the data collection....... In this paper we investigate the robustness of the newly proposed authenticity method introduced by the authors based on second generation multiresolution analysis. This is done by modelling a number of realistic factors that can occur in the data collection....
Attractive ellipsoids in robust control
Poznyak, Alexander; Azhmyakov, Vadim
2014-01-01
This monograph introduces a newly developed robust-control design technique for a wide class of continuous-time dynamical systems called the “attractive ellipsoid method.” Along with a coherent introduction to the proposed control design and related topics, the monograph studies nonlinear affine control systems in the presence of uncertainty and presents a constructive and easily implementable control strategy that guarantees certain stability properties. The authors discuss linear-style feedback control synthesis in the context of the above-mentioned systems. The development and physical implementation of high-performance robust-feedback controllers that work in the absence of complete information is addressed, with numerous examples to illustrate how to apply the attractive ellipsoid method to mechanical and electromechanical systems. While theorems are proved systematically, the emphasis is on understanding and applying the theory to real-world situations. Attractive Ellipsoids in Robust Control will a...
Robustness of holonomic quantum gates
International Nuclear Information System (INIS)
Solinas, P.; Zanardi, P.; Zanghi, N.
2005-01-01
Full text: If the driving field fluctuates during the quantum evolution this produces errors in the applied operator. The holonomic (and geometrical) quantum gates are believed to be robust against some kind of noise. Because of the geometrical dependence of the holonomic operators can be robust against this kind of noise; in fact if the fluctuations are fast enough they cancel out leaving the final operator unchanged. I present the numerical studies of holonomic quantum gates subject to this parametric noise, the fidelity of the noise and ideal evolution is calculated for different noise correlation times. The holonomic quantum gates seem robust not only for fast fluctuating fields but also for slow fluctuating fields. These results can be explained as due to the geometrical feature of the holonomic operator: for fast fluctuating fields the fluctuations are canceled out, for slow fluctuating fields the fluctuations do not perturb the loop in the parameter space. (author)
Robustness in Railway Operations (RobustRailS)
DEFF Research Database (Denmark)
Jensen, Jens Parbo; Nielsen, Otto Anker
This study considers the problem of enhancing railway timetable robustness without adding slack time, hence increasing the travel time. The approach integrates a transit assignment model to assess how passengers adapt their behaviour whenever operations are changed. First, the approach considers...
Effect of robust torus on the dynamical transport
International Nuclear Information System (INIS)
Martins, C G L; Carvalho, R Egydio de; Caldas, I L; Roberto, M
2010-01-01
In the present work, we quantify the fraction of trajectories that reach a specific region of the phase space when we vary a control parameter using two symplectic maps: one non-twist and another one twist. The two maps were studied with and without a robust torus. We compare the obtained patterns and we identify the effect of the robust torus on the dynamical transport. We show that the effect of meandering-like barriers loses importance in blocking the radial transport when the robust torus is present.
Robustness of the ATLAS pixel clustering neural network algorithm
AUTHOR|(INSPIRE)INSPIRE-00407780; The ATLAS collaboration
2016-01-01
Proton-proton collisions at the energy frontier puts strong constraints on track reconstruction algorithms. In the ATLAS track reconstruction algorithm, an artificial neural network is utilised to identify and split clusters of neighbouring read-out elements in the ATLAS pixel detector created by multiple charged particles. The robustness of the neural network algorithm is presented, probing its sensitivity to uncertainties in the detector conditions. The robustness is studied by evaluating the stability of the algorithm's performance under a range of variations in the inputs to the neural networks. Within reasonable variation magnitudes, the neural networks prove to be robust to most variation types.
A Robust Design Applicability Model
DEFF Research Database (Denmark)
Ebro, Martin; Lars, Krogstie; Howard, Thomas J.
2015-01-01
to be applicable in organisations assigning a high importance to one or more factors that are known to be impacted by RD, while also experiencing a high level of occurrence of this factor. The RDAM supplements existing maturity models and metrics to provide a comprehensive set of data to support management......This paper introduces a model for assessing the applicability of Robust Design (RD) in a project or organisation. The intention of the Robust Design Applicability Model (RDAM) is to provide support for decisions by engineering management considering the relevant level of RD activities...
Srivastava, Amit Kumar; Kapoor, Kalpesh
2017-01-01
Let Q be the set of primitive words over a finite alphabet with at least two symbols. We characterize a class of primitive words, Q_I, referred to as ins-robust primitive words, which remain primitive on insertion of any letter from the alphabet and present some properties that characterizes words in the set Q_I. It is shown that the language Q_I is dense. We prove that the language of primitive words that are not ins-robust is not context-free. We also present a linear time algorithm to reco...
Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City
Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo
2014-05-01
The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen
Multivariate Statistical Process Control
DEFF Research Database (Denmark)
Kulahci, Murat
2013-01-01
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...
Robust data reconciliation with TEMPO
International Nuclear Information System (INIS)
Sunde, Svein; Banati, Jozsef
2004-03-01
The Halden Project's TEMPO system is devised to meet the increasing challenges facing utilities in performance monitoring and optimisation, among other things due to deregulation and market liberalisation. The data reconciliation mode is an important one in the TEMPO system. Data reconciliation is a method to provide reliable estimates of process states, parameters, the state of equipment and instruments, and efficiency. Data reconciliation follows maximum likelihood principles, and is usually based on a Gaussian error model for the data. Data reconciliation thus estimates the most likely state of the process, given the heat and mass balance and the current instrument readings. If the assumption of normally (Gaussian) distributed errors in the measurements break down, as it will in the case of gross errors (outliers) in the data set, this needs to be detected by the monitoring system. TEMPO does this by computing an overall test statistic subjected to a hypothesis test, resulting in the so-called goodness-of-fit. If the goodness-of-fit takes a too low value, a fault is probably present in the process. Identifying the location of the fault is more difficult, however. With the Gaussian error model this is still possible employing a so-called serial elimination method. The serial elimination method is, however, cumbersome to use and leads to quite lengthy calculations. The present report describes the application of alternative distributions in the maximum likelihood estimation in an attempt to directly identify the location of faulty sensors. For direct identification of sensor faults significant improvements over the method based on a Gaussian error model has been achieved. However, serial elimination still leads to the highest success rate for fault identification. All results were based on Monte Carlo simulations. (Author)
A robust human face detection algorithm
Raviteja, Thaluru; Karanam, Srikrishna; Yeduguru, Dinesh Reddy V.
2012-01-01
Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.
Robust indexing for automatic data collection
International Nuclear Information System (INIS)
Sauter, Nicholas K.; Grosse-Kunstleve, Ralf W.; Adams, Paul D.
2003-01-01
We present improved methods for indexing diffraction patterns from macromolecular crystals. The novel procedures include a more robust way to verify the position of the incident X-ray beam on the detector, an algorithm to verify that the deduced lattice basis is consistent with the observations, and an alternative approach to identify the metric symmetry of the lattice. These methods help to correct failures commonly experienced during indexing, and increase the overall success rate of the process. Rapid indexing, without the need for visual inspection, will play an important role as beamlines at synchrotron sources prepare for high-throughput automation
Characterizing and predicting the robustness of power-law networks
International Nuclear Information System (INIS)
LaRocca, Sarah; Guikema, Seth D.
2015-01-01
Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2000 randomly-generated power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing networks such as the Internet and cellular metabolic pathways, and efficiently degrading networks such as terrorist cells. - Highlights: • Examine relationship between network topology and robustness to failures. • Relationship is statistically significant for scale-free networks. • Use statistical models to estimate robustness to failures for real-world networks
Essays on robust asset pricing
Horváth, Ferenc
2017-01-01
The central concept of this doctoral dissertation is robustness. I analyze how model and parameter uncertainty affect financial decisions of investors and fund managers, and what their equilibrium consequences are. Chapter 1 gives an overview of the most important concepts and methodologies used in
Robustness of raw quantum tomography
Asorey, M.; Facchi, P.; Florio, G.; Man'ko, V. I.; Marmo, G.; Pascazio, S.; Sudarshan, E. C. G.
2011-01-01
We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.
Robustness of raw quantum tomography
Energy Technology Data Exchange (ETDEWEB)
Asorey, M. [Departamento de Fisica Teorica, Facultad de Ciencias, Universidad de Zaragoza, 50009 Zaragoza (Spain); Facchi, P. [Dipartimento di Matematica, Universita di Bari, I-70125 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Florio, G. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Man' ko, V.I., E-mail: manko@lebedev.r [P.N. Lebedev Physical Institute, Leninskii Prospect 53, Moscow 119991 (Russian Federation); Marmo, G. [Dipartimento di Scienze Fisiche, Universita di Napoli ' Federico II' , I-80126 Napoli (Italy); INFN, Sezione di Napoli, I-80126 Napoli (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Pascazio, S. [Dipartimento di Fisica, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); MECENAS, Universita Federico II di Napoli and Universita di Bari (Italy); Sudarshan, E.C.G. [Department of Physics, University of Texas, Austin, TX 78712 (United States)
2011-01-31
We scrutinize the effects of non-ideal data acquisition on the tomograms of quantum states. The presence of a weight function, schematizing the effects of a finite window or equivalently noise, only affects the state reconstruction procedure by a normalization constant. The results are extended to a discrete mesh and show that quantum tomography is robust under incomplete and approximate knowledge of tomograms.
Aspects of robust linear regression
Davies, P.L.
1993-01-01
Section 1 of the paper contains a general discussion of robustness. In Section 2 the influence function of the Hampel-Rousseeuw least median of squares estimator is derived. Linearly invariant weak metrics are constructed in Section 3. It is shown in Section 4 that $S$-estimators satisfy an exact
Manipulation Robustness of Collaborative Filtering
Benjamin Van Roy; Xiang Yan
2010-01-01
A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions and hence have become targets of manipulation by unscrupulous vendors. We demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust.
Robustness Regions for Dichotomous Decisions.
Vijn, Pieter; Molenaar, Ivo W.
1981-01-01
In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)
Theoretical Framework for Robustness Evaluation
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard
2011-01-01
This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, althou...
Robust control design with MATLAB
Gu, Da-Wei; Konstantinov, Mihail M
2013-01-01
Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: · rewritten and simplified presentation of theoretical and meth...
Robust Portfolio Optimization Using Pseudodistances
2015-01-01
The presence of outliers in financial asset returns is a frequently occurring phenomenon which may lead to unreliable mean-variance optimized portfolios. This fact is due to the unbounded influence that outliers can have on the mean returns and covariance estimators that are inputs in the optimization procedure. In this paper we present robust estimators of mean and covariance matrix obtained by minimizing an empirical version of a pseudodistance between the assumed model and the true model underlying the data. We prove and discuss theoretical properties of these estimators, such as affine equivariance, B-robustness, asymptotic normality and asymptotic relative efficiency. These estimators can be easily used in place of the classical estimators, thereby providing robust optimized portfolios. A Monte Carlo simulation study and applications to real data show the advantages of the proposed approach. We study both in-sample and out-of-sample performance of the proposed robust portfolios comparing them with some other portfolios known in literature. PMID:26468948
Sparse and Robust Factor Modelling
C. Croux (Christophe); P. Exterkate (Peter)
2011-01-01
textabstractFactor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having
Robust distributed cognitive relay beamforming
Pandarakkottilil, Ubaidulla; Aissa, Sonia
2012-01-01
design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can
Approximability of Robust Network Design
Olver, N.K.; Shepherd, F.B.
2014-01-01
We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the
Enhancing Dairy Manufacturing through customer feedback: A statistical approach
Vineesh, D.; Anbuudayasankar, S. P.; Narassima, M. S.
2018-02-01
Dairy products have become inevitable of habitual diet. This study aims to investigate the consumers’ satisfaction towards dairy products so as to provide useful information for the manufacturers which would serve as useful inputs for enriching the quality of products delivered. The study involved consumers of dairy products from various demographical backgrounds across South India. The questionnaire focussed on quality aspects of dairy products and also the service provided. A customer satisfaction model was developed based on various factors identified, with robust hypotheses that govern the use of the product. The developed model proved to be statistically significant as it passed the required statistical tests for reliability, construct validity and interdependency between the constructs. Some major concerns detected were regarding the fat content, taste and odour of packaged milk. A minor proportion of people (15.64%) were unsatisfied with the quality of service provided, which is another issue to be addressed to eliminate the sense of dissatisfaction in the minds of consumers.
Robust topology optimization accounting for geometric imperfections
DEFF Research Database (Denmark)
Schevenels, M.; Jansen, M.; Lombaert, Geert
2013-01-01
performance. As a consequence, the actual structure may be far from optimal. In this paper, a robust approach to topology optimization is presented, taking into account two types of geometric imperfections: variations of (1) the crosssections and (2) the locations of structural elements. The first type...... is modeled by means of a scalar non-Gaussian random field, which is represented as a translation process. The underlying Gaussian field is simulated by means of the EOLE method. The second type of imperfections is modeled as a Gaussian vector-valued random field, which is simulated directly by means...... of the EOLE method. In each iteration of the optimization process, the relevant statistics of the structural response are evaluated by means of a Monte Carlo simulation. The proposed methodology is successfully applied to a test problem involving the design of a compliant mechanism (for the first type...
ROBUST CYLINDER FITTING IN THREE-DIMENSIONAL POINT CLOUD DATA
Directory of Open Access Journals (Sweden)
A. Nurunnabi
2017-05-01
Full Text Available This paper investigates the problems of cylinder fitting in laser scanning three-dimensional Point Cloud Data (PCD. Most existing methods require full cylinder data, do not study the presence of outliers, and are not statistically robust. But especially mobile laser scanning often has incomplete data, as street poles for example are only scanned from the road. Moreover, existence of outliers is common. Outliers may occur as random or systematic errors, and may be scattered and/or clustered. In this paper, we present a statistically robust cylinder fitting algorithm for PCD that combines Robust Principal Component Analysis (RPCA with robust regression. Robust principal components as obtained by RPCA allow estimating cylinder directions more accurately, and an existing efficient circle fitting algorithm following robust regression principles, properly fit cylinder. We demonstrate the performance of the proposed method on artificial and real PCD. Results show that the proposed method provides more accurate and robust results: (i in the presence of noise and high percentage of outliers, (ii for incomplete as well as complete data, (iii for small and large number of points, and (iv for different sizes of radius. On 1000 simulated quarter cylinders of 1m radius with 10% outliers a PCA based method fit cylinders with a radius of on average 3.63 meter (m; the proposed method on the other hand fit cylinders of on average 1.02 m radius. The algorithm has potential in applications such as fitting cylindrical (e.g., light and traffic poles, diameter at breast height estimation for trees, and building and bridge information modelling.
International Nuclear Information System (INIS)
Zhao Yi; Small, Michael; Coward, David; Howell, Eric; Zhao Chunnong; Ju Li; Blair, David
2006-01-01
We describe the application of complexity estimation and the surrogate data method to identify deterministic dynamics in simulated gravitational wave (GW) data contaminated with white and coloured noises. The surrogate method uses algorithmic complexity as a discriminating statistic to decide if noisy data contain a statistically significant level of deterministic dynamics (the GW signal). The results illustrate that the complexity method is sensitive to a small amplitude simulated GW background (SNR down to 0.08 for white noise and 0.05 for coloured noise) and is also more robust than commonly used linear methods (autocorrelation or Fourier analysis)
A robust regression based on weighted LSSVM and penalized trimmed squares
International Nuclear Information System (INIS)
Liu, Jianyong; Wang, Yong; Fu, Chengqun; Guo, Jie; Yu, Qin
2016-01-01
Least squares support vector machine (LS-SVM) for nonlinear regression is sensitive to outliers in the field of machine learning. Weighted LS-SVM (WLS-SVM) overcomes this drawback by adding weight to each training sample. However, as the number of outliers increases, the accuracy of WLS-SVM may decrease. In order to improve the robustness of WLS-SVM, a new robust regression method based on WLS-SVM and penalized trimmed squares (WLSSVM–PTS) has been proposed. The algorithm comprises three main stages. The initial parameters are obtained by least trimmed squares at first. Then, the significant outliers are identified and eliminated by the Fast-PTS algorithm. The remaining samples with little outliers are estimated by WLS-SVM at last. The statistical tests of experimental results carried out on numerical datasets and real-world datasets show that the proposed WLSSVM–PTS is significantly robust than LS-SVM, WLS-SVM and LSSVM–LTS.
Centrality Robustness and Link Prediction in Complex Social Networks
DEFF Research Database (Denmark)
Davidsen, Søren Atmakuri; Ortiz-Arroyo, Daniel
2012-01-01
. Secondly, we present a method to predict edges in dynamic social networks. Our experimental results indicate that the robustness of the centrality measures applied to more realistic social networks follows a predictable pattern and that the use of temporal statistics could improve the accuracy achieved......This chapter addresses two important issues in social network analysis that involve uncertainty. Firstly, we present am analysis on the robustness of centrality measures that extend the work presented in Borgati et al. using three types of complex network structures and one real social network...
Multitarget Approaches to Robust Navigation
National Aeronautics and Space Administration — The performance, stability, and statistical consistency of a vehicle's navigation algorithm are vitally important to the success and safety of its mission....
DEFF Research Database (Denmark)
Kemmler, S.; Eifler, Tobias; Bertsche, B.
2015-01-01
products are and vice versa. For a comprehensive understanding and to use existing synergies between both domains, this paper discusses the basic principles of Reliability- and Robust Design theory. The development of a comprehensive model will enable an integrated consideration of both domains...
Statistics in the pharmacy literature.
Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R
2004-09-01
Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.
Advanced Vibration Analysis Tool Developed for Robust Engine Rotor Designs
Min, James B.
2005-01-01
The primary objective of this research program is to develop vibration analysis tools, design tools, and design strategies to significantly improve the safety and robustness of turbine engine rotors. Bladed disks in turbine engines always feature small, random blade-to-blade differences, or mistuning. Mistuning can lead to a dramatic increase in blade forced-response amplitudes and stresses. Ultimately, this results in high-cycle fatigue, which is a major safety and cost concern. In this research program, the necessary steps will be taken to transform a state-of-the-art vibration analysis tool, the Turbo- Reduce forced-response prediction code, into an effective design tool by enhancing and extending the underlying modeling and analysis methods. Furthermore, novel techniques will be developed to assess the safety of a given design. In particular, a procedure will be established for using natural-frequency curve veerings to identify ranges of operating conditions (rotational speeds and engine orders) in which there is a great risk that the rotor blades will suffer high stresses. This work also will aid statistical studies of the forced response by reducing the necessary number of simulations. Finally, new strategies for improving the design of rotors will be pursued.
Directory of Open Access Journals (Sweden)
Daniela ŞTEFĂNESCU
2011-08-01
Full Text Available The issues referring to official statistics quality and reliability became the main topics of debates as far as statistical governance in Europe is concerned. The Council welcomed the Commission Communication to the European Parliament and to the Council « Towards robust quality management for European Statistics » (COM 211, appreciating that the approach and the objective of the strategy would confer the European Statistical System (ESS the quality management framework for the coordination of consolidated economic policies. The Council pointed out that the European Statistical System management was improved during recent years, that progress was noticed in relation with high quality statistics production and dissemination within the European Union, but has also noticed that, in the context of recent financial crisis, certain weaknesses were identified, particularly related to quality management general framework.„Greece Case” proved that progresses were not enough for guaranteeing the complete independence of national statistical institutes and entailed the need for further consolidating ESS governance. Several undertakings are now in the preparatory stage, in accordance with the Commission Communication; these actions are welcomed, but the question arise: are these sufficient for definitively solving the problem?The paper aims to go ahead in the attempt of identifying a different way, innovative (courageous! on the long run, towards an advanced institutional structure of ESS, by setting up the European System of Statistical Institutes, similar to the European System of Central Banks, that would require a change in the Treaty.
Robust Watermarking of Video Streams
Directory of Open Access Journals (Sweden)
T. Polyák
2006-01-01
Full Text Available In the past few years there has been an explosion in the use of digital video data. Many people have personal computers at home, and with the help of the Internet users can easily share video files on their computer. This makes possible the unauthorized use of digital media, and without adequate protection systems the authors and distributors have no means to prevent it.Digital watermarking techniques can help these systems to be more effective by embedding secret data right into the video stream. This makes minor changes in the frames of the video, but these changes are almost imperceptible to the human visual system. The embedded information can involve copyright data, access control etc. A robust watermark is resistant to various distortions of the video, so it cannot be removed without affecting the quality of the host medium. In this paper I propose a video watermarking scheme that fulfills the requirements of a robust watermark.
Robust Decentralized Formation Flight Control
Directory of Open Access Journals (Sweden)
Zhao Weihua
2011-01-01
Full Text Available Motivated by the idea of multiplexed model predictive control (MMPC, this paper introduces a new framework for unmanned aerial vehicles (UAVs formation flight and coordination. Formulated using MMPC approach, the whole centralized formation flight system is considered as a linear periodic system with control inputs of each UAV subsystem as its periodic inputs. Divided into decentralized subsystems, the whole formation flight system is guaranteed stable if proper terminal cost and terminal constraints are added to each decentralized MPC formulation of the UAV subsystem. The decentralized robust MPC formulation for each UAV subsystem with bounded input disturbances and model uncertainties is also presented. Furthermore, an obstacle avoidance control scheme for any shape and size of obstacles, including the nonapriorily known ones, is integrated under the unified MPC framework. The results from simulations demonstrate that the proposed framework can successfully achieve robust collision-free formation flights.
Salmon: Robust Proxy Distribution for Censorship Circumvention
Directory of Open Access Journals (Sweden)
Douglas Frederick
2016-10-01
Full Text Available Many governments block their citizens’ access to much of the Internet. Simple workarounds are unreliable; censors quickly discover and patch them. Previously proposed robust approaches either have non-trivial obstacles to deployment, or rely on low-performance covert channels that cannot support typical Internet usage such as streaming video. We present Salmon, an incrementally deployable system designed to resist a censor with the resources of the “Great Firewall” of China. Salmon relies on a network of volunteers in uncensored countries to run proxy servers. Although any member of the public can become a user, Salmon protects the bulk of its servers from being discovered and blocked by the censor via an algorithm for quickly identifying malicious users. The algorithm entails identifying some users as especially trustworthy or suspicious, based on their actions. We impede Sybil attacks by requiring either an unobtrusive check of a social network account, or a referral from a trustworthy user.
Inefficient but robust public leadership.
Matsumura, Toshihiro; Ogawa, Akira
2014-01-01
We investigate endogenous timing in a mixed duopoly in a differentiated product market. We find that private leadership is better than public leadership from a social welfare perspective if the private firm is domestic, regardless of the degree of product differentiation. Nevertheless, the public leadership equilibrium is risk-dominant, and it is thus robust if the degree of product differentiation is high. We also find that regardless of the degree of product differentiation, the public lead...
Robust power system frequency control
Bevrani, Hassan
2014-01-01
This updated edition of the industry standard reference on power system frequency control provides practical, systematic and flexible algorithms for regulating load frequency, offering new solutions to the technical challenges introduced by the escalating role of distributed generation and renewable energy sources in smart electric grids. The author emphasizes the physical constraints and practical engineering issues related to frequency in a deregulated environment, while fostering a conceptual understanding of frequency regulation and robust control techniques. The resulting control strategi
Observation Quality Control with a Robust Ensemble Kalman Filter
Roh, Soojin
2013-12-01
Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
Observation Quality Control with a Robust Ensemble Kalman Filter
Roh, Soojin; Genton, Marc G.; Jun, Mikyoung; Szunyogh, Istvan; Hoteit, Ibrahim
2013-01-01
Current ensemble-based Kalman filter (EnKF) algorithms are not robust to gross observation errors caused by technical or human errors during the data collection process. In this paper, the authors consider two types of gross observational errors, additive statistical outliers and innovation outliers, and introduce a method to make EnKF robust to gross observation errors. Using both a one-dimensional linear system of dynamics and a 40-variable Lorenz model, the performance of the proposed robust ensemble Kalman filter (REnKF) was tested and it was found that the new approach greatly improves the performance of the filter in the presence of gross observation errors and leads to only a modest loss of accuracy with clean, outlier-free, observations.
... Watchdog Ratings Feedback Contact Select Page Childhood Cancer Statistics Home > Cancer Resources > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses Incidence Rates ...
The natural statistics of audiovisual speech.
Directory of Open Access Journals (Sweden)
Chandramouli Chandrasekaran
2009-07-01
Full Text Available Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, it's been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2-7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver.
Subset Statistics in the linear IV regression model
Kleibergen, F.R.
2005-01-01
We show that the limiting distributions of subset generalizations of the weak instrument robust instrumental variable statistics are boundedly similar when the remaining structural parameters are estimated using maximum likelihood. They are bounded from above by the limiting distributions which
Robustness Analysis of Timber Truss Structure
DEFF Research Database (Denmark)
Rajčić, Vlatka; Čizmar, Dean; Kirkegaard, Poul Henning
2010-01-01
The present paper discusses robustness of structures in general and the robustness requirements given in the codes. Robustness of timber structures is also an issues as this is closely related to Working group 3 (Robustness of systems) of the COST E55 project. Finally, an example of a robustness...... evaluation of a widespan timber truss structure is presented. This structure was built few years ago near Zagreb and has a span of 45m. Reliability analysis of the main members and the system is conducted and based on this a robustness analysis is preformed....
... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2018 Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard ...
State Transportation Statistics 2014
2014-12-15
The Bureau of Transportation Statistics (BTS) presents State Transportation Statistics 2014, a statistical profile of transportation in the 50 states and the District of Columbia. This is the 12th annual edition of State Transportation Statistics, a ...
A robust bayesian estimate of the concordance correlation coefficient.
Feng, Dai; Baumgartner, Richard; Svetnik, Vladimir
2015-01-01
A need for assessment of agreement arises in many situations including statistical biomarker qualification or assay or method validation. Concordance correlation coefficient (CCC) is one of the most popular scaled indices reported in evaluation of agreement. Robust methods for CCC estimation currently present an important statistical challenge. Here, we propose a novel Bayesian method of robust estimation of CCC based on multivariate Student's t-distribution and compare it with its alternatives. Furthermore, we extend the method to practically relevant settings, enabling incorporation of confounding covariates and replications. The superiority of the new approach is demonstrated using simulation as well as real datasets from biomarker application in electroencephalography (EEG). This biomarker is relevant in neuroscience for development of treatments for insomnia.
Soliton robustness in optical fibers
International Nuclear Information System (INIS)
Menyuk, C.R.
1993-01-01
Simulations and experiments indicate that solitons in optical fibers are robust in the presence of Hamiltonian deformations such as higher-order dispersion and birefringence but are destroyed in the presence of non-Hamiltonian deformations such as attenuation and the Raman effect. Two hypotheses are introduced that generalize these observations and give a recipe for when deformations will be Hamiltonian. Concepts from nonlinear dynamics are used to make these two hypotheses plausible. Soliton stabilization with frequency filtering is also briefly discussed from this point of view
Robust and Sparse Factor Modelling
DEFF Research Database (Denmark)
Croux, Christophe; Exterkate, Peter
Factor construction methods are widely used to summarize a large panel of variables by means of a relatively small number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness to outliers and of sparsity; that is, having relatively few...... nonzero factor loadings. Compared to the traditional factor construction method, we find that this procedure leads to a favorable forecasting performance in the presence of outliers and to better interpretable factors. We investigate the performance of the method in a Monte Carlo experiment...
Robustness Evaluation of Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; čizmar, D.
2010-01-01
The present paper outlines results from working group 3 (WG3) in the EU COST Action E55 – ‘Modelling of the performance of timber structures’. The objectives of the project are related to the three main research activities: the identification and modelling of relevant load and environmental...... exposure scenarios, the improvement of knowledge concerning the behaviour of timber structural elements and the development of a generic framework for the assessment of the life-cycle vulnerability and robustness of timber structures....
Sustainable Resilient, Robust & Resplendent Enterprises
DEFF Research Database (Denmark)
Edgeman, Rick
to their impact. Resplendent enterprises are introduced with resplendence referring not to some sort of public or private façade, but instead refers to organizations marked by dual brilliance and nobility of strategy, governance and comportment that yields superior and sustainable triple bottom line performance....... Herein resilience, robustness, and resplendence (R3) are integrated with sustainable enterprise excellence (Edgeman and Eskildsen, 2013) or SEE and social-ecological innovation (Eskildsen and Edgeman, 2012) to aid progress of a firm toward producing continuously relevant performance that proceed from...
Robust Fringe Projection Profilometry via Sparse Representation.
Budianto; Lun, Daniel P K
2016-04-01
In this paper, a robust fringe projection profilometry (FPP) algorithm using the sparse dictionary learning and sparse coding techniques is proposed. When reconstructing the 3D model of objects, traditional FPP systems often fail to perform if the captured fringe images have a complex scene, such as having multiple and occluded objects. It introduces great difficulty to the phase unwrapping process of an FPP system that can result in serious distortion in the final reconstructed 3D model. For the proposed algorithm, it encodes the period order information, which is essential to phase unwrapping, into some texture patterns and embeds them to the projected fringe patterns. When the encoded fringe image is captured, a modified morphological component analysis and a sparse classification procedure are performed to decode and identify the embedded period order information. It is then used to assist the phase unwrapping process to deal with the different artifacts in the fringe images. Experimental results show that the proposed algorithm can significantly improve the robustness of an FPP system. It performs equally well no matter the fringe images have a simple or complex scene, or are affected due to the ambient lighting of the working environment.
Berchtold, Waldemar; Schäfer, Marcel; Rettig, Michael; Steinebach, Martin
2014-02-01
3D models and applications are of utmost interest in both science and industry. With the increment of their usage, their number and thereby the challenge to correctly identify them increases. Content identification is commonly done by cryptographic hashes. However, they fail as a solution in application scenarios such as computer aided design (CAD), scientific visualization or video games, because even the smallest alteration of the 3D model, e.g. conversion or compression operations, massively changes the cryptographic hash as well. Therefore, this work presents a robust hashing algorithm for 3D mesh data. The algorithm applies several different bit extraction methods. They are built to resist desired alterations of the model as well as malicious attacks intending to prevent correct allocation. The different bit extraction methods are tested against each other and, as far as possible, the hashing algorithm is compared to the state of the art. The parameters tested are robustness, security and runtime performance as well as False Acceptance Rate (FAR) and False Rejection Rate (FRR), also the probability calculation of hash collision is included. The introduced hashing algorithm is kept adaptive e.g. in hash length, to serve as a proper tool for all applications in practice.
Infants generalize representations of statistically segmented words
Directory of Open Access Journals (Sweden)
Katharine eGraf Estes
2012-10-01
Full Text Available The acoustic variation in language presents learners with a substantial challenge. To learn by tracking statistical regularities in speech, infants must recognize words across tokens that differ based on characteristics such as the speaker’s voice, affect, or the sentence context. Previous statistical learning studies have not investigated how these types of surface form variation affect learning. The present experiments used tasks tailored to two distinct developmental levels to investigate the robustness of statistical learning to variation. Experiment 1 examined statistical word segmentation in 11-month-olds and found that infants can recognize statistically segmented words across a change in the speaker’s voice from segmentation to testing. The direction of infants’ preferences suggests that recognizing words across a voice change is more difficult than recognizing them in a consistent voice. Experiment 2 tested whether 17-month-olds can generalize the output of statistical learning across variation to support word learning. The infants were successful in their generalization; they associated referents with statistically defined words despite a change in voice from segmentation to label learning. Infants’ learning patterns also indicate that they formed representations of across-word syllable sequences during segmentation. Thus, low probability sequences can act as object labels in some conditions. The findings of these experiments suggest that the units that emerge during statistical learning are not perceptually constrained, but rather are robust to naturalistic acoustic variation.
Statistics for Learning Genetics
Charles, Abigail Sheena
This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing statistically-based genetics problems. This issue is at the emerging edge of modern college-level genetics instruction, and this study attempts to identify key theoretical components for creating a specialized biological statistics curriculum. The goal of this curriculum will be to prepare biology students with the skills for assimilating quantitatively-based genetic processes, increasingly at the forefront of modern genetics. To fulfill this, two college level classes at two universities were surveyed. One university was located in the northeastern US and the other in the West Indies. There was a sample size of 42 students and a supplementary interview was administered to a select 9 students. Interviews were also administered to professors in the field in order to gain insight into the teaching of statistics in genetics. Key findings indicated that students had very little to no background in statistics (55%). Although students did perform well on exams with 60% of the population receiving an A or B grade, 77% of them did not offer good explanations on a probability question associated with the normal distribution provided in the survey. The scope and presentation of the applicable statistics/mathematics in some of the most used textbooks in genetics teaching, as well as genetics syllabi used by instructors do not help the issue. It was found that the text books, often times, either did not give effective explanations for students, or completely left out certain topics. The omission of certain statistical/mathematical oriented topics was seen to be also true with the genetics syllabi reviewed for this study. Nonetheless
Small Sample Robust Testing for Normality against Pareto Tails
Czech Academy of Sciences Publication Activity Database
Stehlík, M.; Fabián, Zdeněk; Střelec, L.
2012-01-01
Roč. 41, č. 7 (2012), s. 1167-1194 ISSN 0361-0918 Grant - others:Aktion(CZ-AT) 51p7, 54p21, 50p14, 54p13 Institutional research plan: CEZ:AV0Z10300504 Keywords : consistency * Hill estimator * t-Hill estimator * location functional * Pareto tail * power comparison * returns * robust tests for normality Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.295, year: 2012
Robust Learning of Fixed-Structure Bayesian Networks
Diakonikolas, Ilias; Kane, Daniel; Stewart, Alistair
2016-01-01
We investigate the problem of learning Bayesian networks in an agnostic model where an $\\epsilon$-fraction of the samples are adversarially corrupted. Our agnostic learning model is similar to -- in fact, stronger than -- Huber's contamination model in robust statistics. In this work, we study the fully observable Bernoulli case where the structure of the network is given. Even in this basic setting, previous learning algorithms either run in exponential time or lose dimension-dependent facto...
Robust Image Analysis of Faces for Genetic Applications
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2010-01-01
Roč. 6, č. 2 (2010), s. 95-102 ISSN 1801-5603 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : object localization * template matching * eye or mouth detection * robust correlation analysis * image denoising Subject RIV: BB - Applied Statistics, Operational Research http://www.ejbi.cz/articles/201012/47/1.html
Robustness of mission plans for unmanned aircraft
Niendorf, Moritz
, and criticalities are derived. This analysis is extended to Euclidean minimum spanning trees. This thesis aims at enabling increased mission performance by providing means of assessing the robustness and optimality of a mission and methods for identifying critical elements. Examples of the application to mission planning in contested environments, cargo aircraft mission planning, multi-objective mission planning, and planning optimal communication topologies for teams of unmanned aircraft are given.
Artificial intelligence approaches in statistics
International Nuclear Information System (INIS)
Phelps, R.I.; Musgrove, P.B.
1986-01-01
The role of pattern recognition and knowledge representation methods from Artificial Intelligence within statistics is considered. Two areas of potential use are identified and one, data exploration, is used to illustrate the possibilities. A method is presented to identify and separate overlapping groups within cluster analysis, using an AI approach. The potential of such ''intelligent'' approaches is stressed
Advanced statistical methods in data science
Chen, Jiahua; Lu, Xuewen; Yi, Grace; Yu, Hao
2016-01-01
This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a fu...
Renyi statistics in equilibrium statistical mechanics
International Nuclear Information System (INIS)
Parvan, A.S.; Biro, T.S.
2010-01-01
The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.
Sampling, Probability Models and Statistical Reasoning Statistical
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...
Perspective: Evolution and detection of genetic robustness
Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.
2003-01-01
Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms
Robust lyapunov controller for uncertain systems
Laleg-Kirati, Taous-Meriem; Elmetennani, Shahrazed
2017-01-01
Various examples of systems and methods are provided for Lyapunov control for uncertain systems. In one example, a system includes a process plant and a robust Lyapunov controller configured to control an input of the process plant. The robust
Robust distributed cognitive relay beamforming
Pandarakkottilil, Ubaidulla
2012-05-01
In this paper, we present a distributed relay beamformer design for a cognitive radio network in which a cognitive (or secondary) transmit node communicates with a secondary receive node assisted by a set of cognitive non-regenerative relays. The secondary nodes share the spectrum with a licensed primary user (PU) node, and each node is assumed to be equipped with a single transmit/receive antenna. The interference to the PU resulting from the transmission from the cognitive nodes is kept below a specified limit. The proposed robust cognitive relay beamformer design seeks to minimize the total relay transmit power while ensuring that the transceiver signal-to-interference- plus-noise ratio and PU interference constraints are satisfied. The proposed design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can be reformulated as a tractable convex optimization problem that can be solved efficiently. Numerical results are provided and illustrate the performance of the proposed designs for different network operating conditions and parameters. © 2012 IEEE.
Robust canonical correlations: A comparative study
Branco, JA; Croux, Christophe; Filzmoser, P; Oliveira, MR
2005-01-01
Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods axe discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study ...
A statistical approach to plasma profile analysis
International Nuclear Information System (INIS)
Kardaun, O.J.W.F.; McCarthy, P.J.; Lackner, K.; Riedel, K.S.
1990-05-01
A general statistical approach to the parameterisation and analysis of tokamak profiles is presented. The modelling of the profile dependence on both the radius and the plasma parameters is discussed, and pertinent, classical as well as robust, methods of estimation are reviewed. Special attention is given to statistical tests for discriminating between the various models, and to the construction of confidence intervals for the parameterised profiles and the associated global quantities. The statistical approach is shown to provide a rigorous approach to the empirical testing of plasma profile invariance. (orig.)
Statistical Model-Based Face Pose Estimation
Institute of Scientific and Technical Information of China (English)
GE Xinliang; YANG Jie; LI Feng; WANG Huahua
2007-01-01
A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.
Production monitoring system for understanding product robustness
DEFF Research Database (Denmark)
Boorla, Srinivasa Murthy; Howard, Thomas J.
2016-01-01
study is used to demonstrate how the monitoring system can be used to efficiently guide corrective action to improve product performance. It is claimed that the monitoring system can be used to dramatically cut the time taken to identify, planand execute corrective action related to typical quality......In the current quality paradigm, the performance of a product is kept within specification by ensuring that its parts are within specification. Product performance is then validated after final assembly. However, this does not control how robust the product performance is, i.e. how much...... it will vary between the specification limits. In this paper, a model for predicting product performance is proposed, taking into account design, assembly and process parameters live from production. This empowers production to maintain final product performance, instead of part quality. The PRECI‐IN case...
Robust adaptive synchronization of general dynamical networks ...
Indian Academy of Sciences (India)
Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 6. Robust ... A robust adaptive synchronization scheme for these general complex networks with multiple delays and uncertainties is established and raised by employing the robust adaptive control principle and the Lyapunov stability theory. We choose ...
Robust portfolio selection under norm uncertainty
Directory of Open Access Journals (Sweden)
Lei Wang
2016-06-01
Full Text Available Abstract In this paper, we consider the robust portfolio selection problem which has a data uncertainty described by the ( p , w $(p,w$ -norm in the objective function. We show that the robust formulation of this problem is equivalent to a linear optimization problem. Moreover, we present some numerical results concerning our robust portfolio selection problem.
A robust standard deviation control chart
Schoonhoven, M.; Does, R.J.M.M.
2012-01-01
This article studies the robustness of Phase I estimators for the standard deviation control chart. A Phase I estimator should be efficient in the absence of contaminations and resistant to disturbances. Most of the robust estimators proposed in the literature are robust against either diffuse
Robust GPS autonomous signal quality monitoring
Ndili, Awele Nnaemeka
The Global Positioning System (GPS), introduced by the U.S. Department of Defense in 1973, provides unprecedented world-wide navigation capabilities through a constellation of 24 satellites in global orbit, each emitting a low-power radio-frequency signal for ranging. GPS receivers track these transmitted signals, computing position to within 30 meters from range measurements made to four satellites. GPS has a wide range of applications, including aircraft, marine and land vehicle navigation. Each application places demands on GPS for various levels of accuracy, integrity, system availability and continuity of service. Radio frequency interference (RFI), which results from natural sources such as TV/FM harmonics, radar or Mobile Satellite Systems (MSS), presents a challenge in the use of GPS, by posing a threat to the accuracy, integrity and availability of the GPS navigation solution. In order to use GPS for integrity-sensitive applications, it is therefore necessary to monitor the quality of the received signal, with the objective of promptly detecting the presence of RFI, and thus provide a timely warning of degradation of system accuracy. This presents a challenge, since the myriad kinds of RFI affect the GPS receiver in different ways. What is required then, is a robust method of detecting GPS accuracy degradation, which is effective regardless of the origin of the threat. This dissertation presents a new method of robust signal quality monitoring for GPS. Algorithms for receiver autonomous interference detection and integrity monitoring are demonstrated. Candidate test statistics are derived from fundamental receiver measurements of in-phase and quadrature correlation outputs, and the gain of the Active Gain Controller (AGC). Performance of selected test statistics are evaluated in the presence of RFI: broadband interference, pulsed and non-pulsed interference, coherent CW at different frequencies; and non-RFI: GPS signal fading due to physical blockage and
Wang, S.; Ancell, B. C.; Huang, G. H.; Baetz, B. W.
2018-03-01
Data assimilation using the ensemble Kalman filter (EnKF) has been increasingly recognized as a promising tool for probabilistic hydrologic predictions. However, little effort has been made to conduct the pre- and post-processing of assimilation experiments, posing a significant challenge in achieving the best performance of hydrologic predictions. This paper presents a unified data assimilation framework for improving the robustness of hydrologic ensemble predictions. Statistical pre-processing of assimilation experiments is conducted through the factorial design and analysis to identify the best EnKF settings with maximized performance. After the data assimilation operation, statistical post-processing analysis is also performed through the factorial polynomial chaos expansion to efficiently address uncertainties in hydrologic predictions, as well as to explicitly reveal potential interactions among model parameters and their contributions to the predictive accuracy. In addition, the Gaussian anamorphosis is used to establish a seamless bridge between data assimilation and uncertainty quantification of hydrologic predictions. Both synthetic and real data assimilation experiments are carried out to demonstrate feasibility and applicability of the proposed methodology in the Guadalupe River basin, Texas. Results suggest that statistical pre- and post-processing of data assimilation experiments provide meaningful insights into the dynamic behavior of hydrologic systems and enhance robustness of hydrologic ensemble predictions.
Ma, Yanyuan
2013-09-01
We propose semiparametric methods to estimate the center and shape of a symmetric population when a representative sample of the population is unavailable due to selection bias. We allow an arbitrary sample selection mechanism determined by the data collection procedure, and we do not impose any parametric form on the population distribution. Under this general framework, we construct a family of consistent estimators of the center that is robust to population model misspecification, and we identify the efficient member that reaches the minimum possible estimation variance. The asymptotic properties and finite sample performance of the estimation and inference procedures are illustrated through theoretical analysis and simulations. A data example is also provided to illustrate the usefulness of the methods in practice. © 2013 American Statistical Association.
Wilkinson, M.H.F.
The Robust Automatic Threshold Selection algorithm was introduced as a threshold selection based on a simple image statistic. The statistic is an average of the grey levels of the pixels in an image weighted by the response at each pixel of a specific edge detector. Other authors have suggested that
Robustness Assessment of Spatial Timber Structures
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning
2012-01-01
Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern buildi...... to robustness of spatial timber structures and will discuss the consequences of such robustness issues related to the future development of timber structures.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. In order to minimise the likelihood of such disproportionate structural failures many modern building...... codes consider the need for robustness of structures and provide strategies and methods to obtain robustness. Therefore a structural engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper summaries issues with respect...
Enabling Rapid and Robust Structural Analysis During Conceptual Design
Eldred, Lloyd B.; Padula, Sharon L.; Li, Wu
2015-01-01
This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.
Modern nonparametric, robust and multivariate methods festschrift in honour of Hannu Oja
Taskinen, Sara
2015-01-01
Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.
Savage, Leonard J
1972-01-01
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
State Transportation Statistics 2010
2011-09-14
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2010, a statistical profile of transportation in the 50 states and the District of Col...
State Transportation Statistics 2012
2013-08-15
The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportation's (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2012, a statistical profile of transportation ...
Adrenal Gland Tumors: Statistics
... Gland Tumor: Statistics Request Permissions Adrenal Gland Tumor: Statistics Approved by the Cancer.Net Editorial Board , 03/ ... primary adrenal gland tumor is very uncommon. Exact statistics are not available for this type of tumor ...
State transportation statistics 2009
2009-01-01
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and : Innovative Technology Administration (RITA), presents State Transportation : Statistics 2009, a statistical profile of transportation in the 50 states and the : District ...
State Transportation Statistics 2011
2012-08-08
The Bureau of Transportation Statistics (BTS), a part of DOTs Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2011, a statistical profile of transportation in the 50 states and the District of Col...
Neuroendocrine Tumor: Statistics
... Tumor > Neuroendocrine Tumor: Statistics Request Permissions Neuroendocrine Tumor: Statistics Approved by the Cancer.Net Editorial Board , 01/ ... the body. It is important to remember that statistics on the survival rates for people with a ...
State Transportation Statistics 2013
2014-09-19
The Bureau of Transportation Statistics (BTS), a part of the U.S. Department of Transportations (USDOT) Research and Innovative Technology Administration (RITA), presents State Transportation Statistics 2013, a statistical profile of transportatio...
BTS statistical standards manual
2005-10-01
The Bureau of Transportation Statistics (BTS), like other federal statistical agencies, establishes professional standards to guide the methods and procedures for the collection, processing, storage, and presentation of statistical data. Standards an...
Robust design principles for reducing variation in functional performance
DEFF Research Database (Denmark)
Christensen, Martin Ebro; Howard, Thomas J.
2016-01-01
This paper identifies, describes and classifies a comprehensive collection of variation reduction principles (VRP) that can be used to increase the robustness of a product and reduce its variation in functional performance. Performance variation has a negative effect on the reliability and percei......This paper identifies, describes and classifies a comprehensive collection of variation reduction principles (VRP) that can be used to increase the robustness of a product and reduce its variation in functional performance. Performance variation has a negative effect on the reliability...... and perceived quality of a product and efforts should be made to minimise it. The design principles are identified by a systematic decomposition of the Taguchi Transfer Function in combination with the use of existing literature and the authors’ experience. The paper presents 15 principles and describes...... their advantages and disadvantages along with example cases. Subsequently, the principles are classified based on their applicability in the various development and production stages. The VRP are to be added to existing robust design methodologies, helping the designer to think beyond robust design tool and method...
Statistical approaches for evaluating body composition markers in clinical cancer research.
Bayar, Mohamed Amine; Antoun, Sami; Lanoy, Emilie
2017-04-01
The term 'morphomics' stands for the markers of body composition in muscle and adipose tissues. in recent years, as part of clinical cancer research, several associations between morphomics and outcome or toxicity were found in different treatment settings leading to a growing interest. we aim to review statistical approaches used to evaluate these markers and suggest practical statistical recommendations. Area covered: We identified statistical methods used recently to take into account properties of morphomics measurements. We also reviewed adjustment methods on major confounding factors such as gender and approaches to model morphomic data, especially mixed models for repeated measures. Finally, we focused on methods for determining a cut-off for a morphomic marker that could be used in clinical practice and how to assess its robustness. Expert commentary: From our review, we proposed 13 key points to strengthen analyses and reporting of clinical research assessing associations between morphomics and outcome or toxicity.
RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks
Energy Technology Data Exchange (ETDEWEB)
Balasundaram, Balabhaskar [Oklahoma State Univ., Stillwater, OK (United States); Butenko, Sergiy [Texas A & M Univ., College Station, TX (United States); Boginski, Vladimir [Univ. of Florida, Gainesville, FL (United States); Uryasev, Stan [Univ. of Florida, Gainesville, FL (United States)
2013-12-25
The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need
Robust network topologies for generating switch-like cellular responses.
Directory of Open Access Journals (Sweden)
Najaf A Shah
2011-06-01
Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.
Robustness Area Technique Developing Guidelines for Power System Restoration
Directory of Open Access Journals (Sweden)
Paulo Murinelli Pesoti
2017-01-01
Full Text Available This paper proposes a novel energy based technique called the Robustness Area (RA technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs. The motivation is on account of the latest blackouts in Brazil, where the local Independent System Operator (ISO encountered difficulties related to circuit disconnections during the restoration. The technique identifies vulnerable and robust buses, pointing out system areas that should be firstly reinforced during PSR, in order to enhance system stability. A Brazilian power system restoration area is used to compare the guidelines adopted by the ISO with a more suitable new plan indicated by the RA tool. Active power and reactive power load margin and standing phase angle show the method efficiency as a result of a well balanced system configuration, enhancing the restoration performance. Time domain simulations for loop closures and severe events also show the positive impact that the proposed tool brings to PSRs.
Integrating robust timetabling in line plan optimization for railway systems
DEFF Research Database (Denmark)
Burggraeve, Sofie; Bull, Simon Henry; Vansteenwegen, Pieter
2017-01-01
We propose a heuristic algorithm to build a railway line plan from scratch that minimizes passenger travel time and operator cost and for which a feasible and robust timetable exists. A line planning module and a timetabling module work iteratively and interactively. The line planning module......, but is constrained by limited shunt capacity. While the operator and passenger cost remain close to those of the initially and (for these costs) optimally built line plan, the timetable corresponding to the finally developed robust line plan significantly improves the minimum buffer time, and thus the robustness...... creates an initial line plan. The timetabling module evaluates the line plan and identifies a critical line based on minimum buffer times between train pairs. The line planning module proposes a new line plan in which the time length of the critical line is modified in order to provide more flexibility...
Robust regularized singular value decomposition with application to mortality data
Zhang, Lingsong
2013-09-01
We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year. The RobRSVD is formulated as a penalized loss minimization problem where a robust loss function is used to measure the reconstruction error of a low-rank matrix approximation of the data, and an appropriately defined two-way roughness penalty function is used to ensure smoothness along each of the two functional domains. By viewing the minimization problem as two conditional regularized robust regressions, we develop a fast iterative reweighted least squares algorithm to implement the method. Our implementation naturally incorporates missing values. Furthermore, our formulation allows rigorous derivation of leaveone- row/column-out cross-validation and generalized cross-validation criteria, which enable computationally efficient data-driven penalty parameter selection. The advantages of the new robust method over nonrobust ones are shown via extensive simulation studies and the mortality rate application. © Institute of Mathematical Statistics, 2013.
On robust parameter estimation in brain-computer interfacing
Samek, Wojciech; Nakajima, Shinichi; Kawanabe, Motoaki; Müller, Klaus-Robert
2017-12-01
Objective. The reliable estimation of parameters such as mean or covariance matrix from noisy and high-dimensional observations is a prerequisite for successful application of signal processing and machine learning algorithms in brain-computer interfacing (BCI). This challenging task becomes significantly more difficult if the data set contains outliers, e.g. due to subject movements, eye blinks or loose electrodes, as they may heavily bias the estimation and the subsequent statistical analysis. Although various robust estimators have been developed to tackle the outlier problem, they ignore important structural information in the data and thus may not be optimal. Typical structural elements in BCI data are the trials consisting of a few hundred EEG samples and indicating the start and end of a task. Approach. This work discusses the parameter estimation problem in BCI and introduces a novel hierarchical view on robustness which naturally comprises different types of outlierness occurring in structured data. Furthermore, the class of minimum divergence estimators is reviewed and a robust mean and covariance estimator for structured data is derived and evaluated with simulations and on a benchmark data set. Main results. The results show that state-of-the-art BCI algorithms benefit from robustly estimated parameters. Significance. Since parameter estimation is an integral part of various machine learning algorithms, the presented techniques are applicable to many problems beyond BCI.
Robust input design for nonlinear dynamic modeling of AUV.
Nouri, Nowrouz Mohammad; Valadi, Mehrdad
2017-09-01
Input design has a dominant role in developing the dynamic model of autonomous underwater vehicles (AUVs) through system identification. Optimal input design is the process of generating informative inputs that can be used to generate the good quality dynamic model of AUVs. In a problem with optimal input design, the desired input signal depends on the unknown system which is intended to be identified. In this paper, the input design approach which is robust to uncertainties in model parameters is used. The Bayesian robust design strategy is applied to design input signals for dynamic modeling of AUVs. The employed approach can design multiple inputs and apply constraints on an AUV system's inputs and outputs. Particle swarm optimization (PSO) is employed to solve the constraint robust optimization problem. The presented algorithm is used for designing the input signals for an AUV, and the estimate obtained by robust input design is compared with that of the optimal input design. According to the results, proposed input design can satisfy both robustness of constraints and optimality. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Robust holographic storage system design.
Watanabe, Takahiro; Watanabe, Minoru
2011-11-21
Demand is increasing daily for large data storage systems that are useful for applications in spacecraft, space satellites, and space robots, which are all exposed to radiation-rich space environment. As candidates for use in space embedded systems, holographic storage systems are promising because they can easily provided the demanded large-storage capability. Particularly, holographic storage systems, which have no rotation mechanism, are demanded because they are virtually maintenance-free. Although a holographic memory itself is an extremely robust device even in a space radiation environment, its associated lasers and drive circuit devices are vulnerable. Such vulnerabilities sometimes engendered severe problems that prevent reading of all contents of the holographic memory, which is a turn-off failure mode of a laser array. This paper therefore presents a proposal for a recovery method for the turn-off failure mode of a laser array on a holographic storage system, and describes results of an experimental demonstration. © 2011 Optical Society of America
Efficient robust conditional random fields.
Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A
2015-10-01
Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.
Thiese, Matthew S; Walker, Skyler; Lindsey, Jenna
2017-10-01
Distribution of valuable research discoveries are needed for the continual advancement of patient care. Publication and subsequent reliance of false study results would be detrimental for patient care. Unfortunately, research misconduct may originate from many sources. While there is evidence of ongoing research misconduct in all it's forms, it is challenging to identify the actual occurrence of research misconduct, which is especially true for misconduct in clinical trials. Research misconduct is challenging to measure and there are few studies reporting the prevalence or underlying causes of research misconduct among biomedical researchers. Reported prevalence estimates of misconduct are probably underestimates, and range from 0.3% to 4.9%. There have been efforts to measure the prevalence of research misconduct; however, the relatively few published studies are not freely comparable because of varying characterizations of research misconduct and the methods used for data collection. There are some signs which may point to an increased possibility of research misconduct, however there is a need for continued self-policing by biomedical researchers. There are existing resources to assist in ensuring appropriate statistical methods and preventing other types of research fraud. These included the "Statistical Analyses and Methods in the Published Literature", also known as the SAMPL guidelines, which help scientists determine the appropriate method of reporting various statistical methods; the "Strengthening Analytical Thinking for Observational Studies", or the STRATOS, which emphases on execution and interpretation of results; and the Committee on Publication Ethics (COPE), which was created in 1997 to deliver guidance about publication ethics. COPE has a sequence of views and strategies grounded in the values of honesty and accuracy.
Isotopic safeguards statistics
International Nuclear Information System (INIS)
Timmerman, C.L.; Stewart, K.B.
1978-06-01
The methods and results of our statistical analysis of isotopic data using isotopic safeguards techniques are illustrated using example data from the Yankee Rowe reactor. The statistical methods used in this analysis are the paired comparison and the regression analyses. A paired comparison results when a sample from a batch is analyzed by two different laboratories. Paired comparison techniques can be used with regression analysis to detect and identify outlier batches. The second analysis tool, linear regression, involves comparing various regression approaches. These approaches use two basic types of models: the intercept model (y = α + βx) and the initial point model [y - y 0 = β(x - x 0 )]. The intercept model fits strictly the exposure or burnup values of isotopic functions, while the initial point model utilizes the exposure values plus the initial or fabricator's data values in the regression analysis. Two fitting methods are applied to each of these models. These methods are: (1) the usual least squares fitting approach where x is measured without error, and (2) Deming's approach which uses the variance estimates obtained from the paired comparison results and considers x and y are both measured with error. The Yankee Rowe data were first measured by Nuclear Fuel Services (NFS) and remeasured by Nuclear Audit and Testing Company (NATCO). The ratio of Pu/U versus 235 D (in which 235 D is the amount of depleted 235 U expressed in weight percent) using actual numbers is the isotopic function illustrated. Statistical results using the Yankee Rowe data indicates the attractiveness of Deming's regression model over the usual approach by simple comparison of the given regression variances with the random variance from the paired comparison results
Robust satellite techniques for monitoring volcanic eruptions
Energy Technology Data Exchange (ETDEWEB)
Pergola, N.; Pietrapertosa, C. [Consiglio Nazionale delle Ricerche, Istituto di Metodologie Avanzate, Tito Scalo, PZ (Italy); Lacava, T.; Tramutoli, V. [Potenza Universita' della Basilicata, Potenza (Italy). Dipt. di Ingegneria e Fisica dell' Ambiente
2001-04-01
Through this paper the robust approach to monitoring volcanic aerosols by satellite is applied to an extended set of events affecting Stromboli and Etna volcanoes to assess its performance in automated detection of eruptive clouds and in monitoring pre-eruptive emission activities. Using only NOAA/AVHRR data at hand (without any specific atmospheric model or ancillary ground-based measurements) the proposed method automatically discriminates meteorological from eruptive volcanic clouds and, in several cases, identified pre-eruptive anomalies in the emission rates not identified by traditional methods. The main merit of this approach is its effectiveness in recognising field anomalies also in the presence of a highly variable surface background as well as its intrinsic exportability not only on different geographic areas but also on different satellite instrumental packages. In particular, the possibility to extend the proposed method to the incoming new MSG/SEVIRI satellite package (which is going to fly next year) with its improved spectral (specific bands for SO{sub 2}) and temporal (up to 15 min) resolutions has been evaluated representing the natural continuation of this work.
Robust AIC with High Breakdown Scale Estimate
Directory of Open Access Journals (Sweden)
Shokrya Saleh
2014-01-01
Full Text Available Akaike Information Criterion (AIC based on least squares (LS regression minimizes the sum of the squared residuals; LS is sensitive to outlier observations. Alternative criterion, which is less sensitive to outlying observation, has been proposed; examples are robust AIC (RAIC, robust Mallows Cp (RCp, and robust Bayesian information criterion (RBIC. In this paper, we propose a robust AIC by replacing the scale estimate with a high breakdown point estimate of scale. The robustness of the proposed methods is studied through its influence function. We show that, the proposed robust AIC is effective in selecting accurate models in the presence of outliers and high leverage points, through simulated and real data examples.
Business Statistics Education: Content and Software in Undergraduate Business Statistics Courses.
Tabatabai, Manouchehr; Gamble, Ralph
1997-01-01
Survey responses from 204 of 500 business schools identified most often topics in business statistics I and II courses. The most popular software at both levels was Minitab. Most schools required both statistics I and II. (SK)
Multimodel Robust Control for Hydraulic Turbine
Osuský, Jakub; Števo, Stanislav
2014-01-01
The paper deals with the multimodel and robust control system design and their combination based on M-Δ structure. Controller design will be done in the frequency domain with nominal performance specified by phase margin. Hydraulic turbine model is analyzed as system with unstructured uncertainty, and robust stability condition is included in controller design. Multimodel and robust control approaches are presented in detail on hydraulic turbine model. Control design approaches are compared a...
Forecasting exchange rates: a robust regression approach
Preminger, Arie; Franck, Raphael
2005-01-01
The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...
Information Statistics in Schools Educate your students about the value and everyday use of statistics. The Statistics in Schools program provides resources for teaching and learning with real life data. Explore the site for standards-aligned, classroom-ready activities. Statistics in Schools Math Activities History
Transport Statistics - Transport - UNECE
Sustainable Energy Statistics Trade Transport Themes UNECE and the SDGs Climate Change Gender Ideas 4 Change UNECE Weekly Videos UNECE Transport Areas of Work Transport Statistics Transport Transport Statistics About us Terms of Reference Meetings and Events Meetings Working Party on Transport Statistics (WP.6
Identifying tectonic parameters that influence tsunamigenesis
van Zelst, Iris; Brizzi, Silvia; van Dinther, Ylona; Heuret, Arnauld; Funiciello, Francesca
2017-04-01
The role of tectonics in tsunami generation is at present poorly understood. However, the fact that some regions produce more tsunamis than others indicates that tectonics could influence tsunamigenesis. Here, we complement a global earthquake database that contains geometrical, mechanical, and seismicity parameters of subduction zones with tsunami data. We statistically analyse the database to identify the tectonic parameters that affect tsunamigenesis. The Pearson's product-moment correlation coefficients reveal high positive correlations of 0.65 between, amongst others, the maximum water height of tsunamis and the seismic coupling in a subduction zone. However, these correlations are mainly caused by outliers. The Spearman's rank correlation coefficient results in more robust correlations of 0.60 between the number of tsunamis in a subduction zone and subduction velocity (positive correlation) and the sediment thickness at the trench (negative correlation). Interestingly, there is a positive correlation between the latter and tsunami magnitude. In an effort towards multivariate statistics, a binary decision tree analysis is conducted with one variable. However, this shows that the amount of data is too scarce. To complement this limited amount of data and to assess physical causality of the tectonic parameters with regard to tsunamigenesis, we conduct a numerical study of the most promising parameters using a geodynamic seismic cycle model. We show that an increase in sediment thickness on the subducting plate results in a shift in seismic activity from outerrise normal faults to splay faults. We also show that the splay fault is the preferred rupture path for a strongly velocity strengthening friction regime in the shallow part of the subduction zone, which increases the tsunamigenic potential. A larger updip limit of the seismogenic zone results in larger vertical surface displacement.
Robust misinterpretation of confidence intervals.
Hoekstra, Rink; Morey, Richard D; Rouder, Jeffrey N; Wagenmakers, Eric-Jan
2014-10-01
Null hypothesis significance testing (NHST) is undoubtedly the most common inferential technique used to justify claims in the social sciences. However, even staunch defenders of NHST agree that its outcomes are often misinterpreted. Confidence intervals (CIs) have frequently been proposed as a more useful alternative to NHST, and their use is strongly encouraged in the APA Manual. Nevertheless, little is known about how researchers interpret CIs. In this study, 120 researchers and 442 students-all in the field of psychology-were asked to assess the truth value of six particular statements involving different interpretations of a CI. Although all six statements were false, both researchers and students endorsed, on average, more than three statements, indicating a gross misunderstanding of CIs. Self-declared experience with statistics was not related to researchers' performance, and, even more surprisingly, researchers hardly outperformed the students, even though the students had not received any education on statistical inference whatsoever. Our findings suggest that many researchers do not know the correct interpretation of a CI. The misunderstandings surrounding p-values and CIs are particularly unfortunate because they constitute the main tools by which psychologists draw conclusions from data.
Robustness: confronting lessons from physics and biology.
Lesne, Annick
2008-11-01
The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.
Robustness of Long Span Reciprocal Timber Structures
DEFF Research Database (Denmark)
Balfroid, Nathalie; Kirkegaard, Poul Henning
2011-01-01
engineer may take necessary steps to design robust structures that are insensitive to accidental circumstances. The present paper makes a discussion of such robustness issues related to the future development of reciprocal timber structures. The paper concludes that these kind of structures can have...... a potential as long span timber structures in real projects if they are carefully designed with respect to the overall robustness strategies.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. The interest has also been facilitated due to recently severe structural failures...
Gupta, Munish; Kaplan, Heather C
2017-09-01
Quality improvement (QI) is based on measuring performance over time, and variation in data measured over time must be understood to guide change and make optimal improvements. Common cause variation is natural variation owing to factors inherent to any process; special cause variation is unnatural variation owing to external factors. Statistical process control methods, and particularly control charts, are robust tools for understanding data over time and identifying common and special cause variation. This review provides a practical introduction to the use of control charts in health care QI, with a focus on neonatology. Copyright © 2017 Elsevier Inc. All rights reserved.
Robust Cyclic MUSIC Algorithm for Finding Directions in Impulsive Noise Environment
Directory of Open Access Journals (Sweden)
Sen Li
2017-01-01
Full Text Available This paper addresses the issue of direction finding of a cyclostationary signal under impulsive noise environments modeled by α-stable distribution. Since α-stable distribution does not have finite second-order statistics, the conventional cyclic correlation-based signal-selective direction finding algorithms do not work effectively. To resolve this problem, we define two robust cyclic correlation functions which are derived from robust statistics property of the correntropy and the nonlinear transformation, respectively. The MUSIC algorithm with the robust cyclic correlation matrix of the received signals of arrays is then used to estimate the direction of cyclostationary signal in the presence of impulsive noise. The computer simulation results demonstrate that the two proposed robust cyclic correlation-based algorithms outperform the conventional cyclic correlation and the fractional lower order cyclic correlation based methods.
Stochastic simulation and robust design optimization of integrated photonic filters
Directory of Open Access Journals (Sweden)
Weng Tsui-Wei
2016-07-01
Full Text Available Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%–35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.
Robust Design Optimization of an Aerospace Vehicle Prolusion System
Directory of Open Access Journals (Sweden)
Muhammad Aamir Raza
2011-01-01
Full Text Available This paper proposes a robust design optimization methodology under design uncertainties of an aerospace vehicle propulsion system. The approach consists of 3D geometric design coupled with complex internal ballistics, hybrid optimization, worst-case deviation, and efficient statistical approach. The uncertainties are propagated through worst-case deviation using first-order orthogonal design matrices. The robustness assessment is measured using the framework of mean-variance and percentile difference approach. A parametric sensitivity analysis is carried out to analyze the effects of design variables variation on performance parameters. A hybrid simulated annealing and pattern search approach is used as an optimizer. The results show the objective function of optimizing the mean performance and minimizing the variation of performance parameters in terms of thrust ratio and total impulse could be achieved while adhering to the system constraints.
A robust dataset-agnostic heart disease classifier from Phonocardiogram.
Banerjee, Rohan; Dutta Choudhury, Anirban; Deshpande, Parijat; Bhattacharya, Sakyajit; Pal, Arpan; Mandana, K M
2017-07-01
Automatic classification of normal and abnormal heart sounds is a popular area of research. However, building a robust algorithm unaffected by signal quality and patient demography is a challenge. In this paper we have analysed a wide list of Phonocardiogram (PCG) features in time and frequency domain along with morphological and statistical features to construct a robust and discriminative feature set for dataset-agnostic classification of normal and cardiac patients. The large and open access database, made available in Physionet 2016 challenge was used for feature selection, internal validation and creation of training models. A second dataset of 41 PCG segments, collected using our in-house smart phone based digital stethoscope from an Indian hospital was used for performance evaluation. Our proposed methodology yielded sensitivity and specificity scores of 0.76 and 0.75 respectively on the test dataset in classifying cardiovascular diseases. The methodology also outperformed three popular prior art approaches, when applied on the same dataset.
Many-objective robust decision making for water allocation under climate change
Yan, Dan; Ludwig, Fulco; Huang, He Qing; Werners, Saskia E.
2017-01-01
Water allocation is facing profound challenges due to climate change uncertainties. To identify adaptive water allocation strategies that are robust to climate change uncertainties, a model framework combining many-objective robust decision making and biophysical modeling is developed for large
Godolphin, JD; Godolphin, EJ
2015-01-01
© 2015 Australian Statistical Publishing Association Inc. Criteria are proposed for assessing the robustness of a binary block design against the loss of whole blocks, based on summing entries of selected upper non-principal sections of the concurrence matrix. These criteria improve on the minimal concurrence concept that has been used previously and provide new conditions for measuring the robustness status of a design. The robustness properties of two-associate partially balanced designs ar...
Generalized quantum statistics
International Nuclear Information System (INIS)
Chou, C.
1992-01-01
In the paper, a non-anyonic generalization of quantum statistics is presented, in which Fermi-Dirac statistics (FDS) and Bose-Einstein statistics (BES) appear as two special cases. The new quantum statistics, which is characterized by the dimension of its single particle Fock space, contains three consistent parts, namely the generalized bilinear quantization, the generalized quantum mechanical description and the corresponding statistical mechanics
QInfer: Statistical inference software for quantum applications
Directory of Open Access Journals (Sweden)
Christopher Granade
2017-04-01
Full Text Available Characterizing quantum systems through experimental data is critical to applications as diverse as metrology and quantum computing. Analyzing this experimental data in a robust and reproducible manner is made challenging, however, by the lack of readily-available software for performing principled statistical analysis. We improve the robustness and reproducibility of characterization by introducing an open-source library, QInfer, to address this need. Our library makes it easy to analyze data from tomography, randomized benchmarking, and Hamiltonian learning experiments either in post-processing, or online as data is acquired. QInfer also provides functionality for predicting the performance of proposed experimental protocols from simulated runs. By delivering easy-to-use characterization tools based on principled statistical analysis, QInfer helps address many outstanding challenges facing quantum technology.
[Big data in official statistics].
Zwick, Markus
2015-08-01
The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.
Robust Linear Models for Cis-eQTL Analysis.
Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C
2015-01-01
Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.
Robust Adaptable Video Copy Detection
DEFF Research Database (Denmark)
Assent, Ira; Kremer, Hardy
2009-01-01
in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models.......Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change...
Super-delta: a new differential gene expression analysis procedure with robust data normalization.
Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing
2017-12-21
Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super
National Statistical Commission and Indian Official Statistics
Indian Academy of Sciences (India)
Author Affiliations. T J Rao1. C. R. Rao Advanced Institute of Mathematics, Statistics and Computer Science (AIMSCS) University of Hyderabad Campus Central University Post Office, Prof. C. R. Rao Road Hyderabad 500 046, AP, India.
Introductory statistics for the behavioral sciences
Welkowitz, Joan; Cohen, Jacob
1971-01-01
Introductory Statistics for the Behavioral Sciences provides an introduction to statistical concepts and principles. This book emphasizes the robustness of parametric procedures wherein such significant tests as t and F yield accurate results even if such assumptions as equal population variances and normal population distributions are not well met.Organized into three parts encompassing 16 chapters, this book begins with an overview of the rationale upon which much of behavioral science research is based, namely, drawing inferences about a population based on data obtained from a samp
A multi-criteria decision making approach to identify a vaccine formulation.
Dewé, Walthère; Durand, Christelle; Marion, Sandie; Oostvogels, Lidia; Devaster, Jeanne-Marie; Fourneau, Marc
2016-01-01
This article illustrates the use of a multi-criteria decision making approach, based on desirability functions, to identify an appropriate adjuvant composition for an influenza vaccine to be used in elderly. The proposed adjuvant system contained two main elements: monophosphoryl lipid and α-tocopherol with squalene in an oil/water emulsion. The objective was to elicit a stronger immune response while maintaining an acceptable reactogenicity and safety profile. The study design, the statistical models, the choice of the desirability functions, the computation of the overall desirability index, and the assessment of the robustness of the ranking are all detailed in this manuscript.
Strong memory in time series of human magnetoencephalograms can identify photosensitive epilepsy
International Nuclear Information System (INIS)
Yulmetyev, R. M.; Yulmetyeva, D. G.; Haenggi, P.; Shimojo, S.; Bhattacharya, J.
2007-01-01
To discuss the salient role of statistical memory effects in human brain functioning, we have analyzed a set of stochastic memory quantifiers that reflects the dynamical characteristics of neuromagnetic responses of magnetoencephalographic signals to a flickering stimulus of different color combinations from a group of control subjects, and compared them with those for a patient with photosensitive epilepsy. We have discovered that the emergence of strong memory and the accompanying transition to a regular and robust regime of chaotic behavior of signals in separate areas for a patient most likely identifies the regions where the protective mechanism against the occurrence of photosensitive epilepsy is located
Robust-BD Estimation and Inference for General Partially Linear Models
Directory of Open Access Journals (Sweden)
Chunming Zhang
2017-11-01
Full Text Available The classical quadratic loss for the partially linear model (PLM and the likelihood function for the generalized PLM are not resistant to outliers. This inspires us to propose a class of “robust-Bregman divergence (BD” estimators of both the parametric and nonparametric components in the general partially linear model (GPLM, which allows the distribution of the response variable to be partially specified, without being fully known. Using the local-polynomial function estimation method, we propose a computationally-efficient procedure for obtaining “robust-BD” estimators and establish the consistency and asymptotic normality of the “robust-BD” estimator of the parametric component β o . For inference procedures of β o in the GPLM, we show that the Wald-type test statistic W n constructed from the “robust-BD” estimators is asymptotically distribution free under the null, whereas the likelihood ratio-type test statistic Λ n is not. This provides an insight into the distinction from the asymptotic equivalence (Fan and Huang 2005 between W n and Λ n in the PLM constructed from profile least-squares estimators using the non-robust quadratic loss. Numerical examples illustrate the computational effectiveness of the proposed “robust-BD” estimators and robust Wald-type test in the appearance of outlying observations.
Structural Robustness Evaluation of Offshore Wind Turbines
DEFF Research Database (Denmark)
Giuliani, Luisa; Bontempi, Franco
2010-01-01
in the framework of a safe design: it depends on different factors, like exposure, vulnerability and robustness. Particularly, the requirement of structural vulnerability and robustness are discussed in this paper and a numerical application is presented, in order to evaluate the effects of a ship collision...
In Silico Design of Robust Bolalipid Membranes
Bulacu, Monica; Periole, Xavier; Marrink, Siewert J.; Périole, Xavier
The robustness of microorganisms used in industrial fermentations is essential for the efficiency and yield of the production process. A viable tool to increase the robustness is through engineering of the cell membrane and especially by incorporating lipids from species that survive under harsh
Assessment of Process Robustness for Mass Customization
DEFF Research Database (Denmark)
Nielsen, Kjeld; Brunø, Thomas Ditlev
2013-01-01
robustness and their capability to develop it. Through literature study and analysis of robust process design characteristics a number of metrics are described which can be used for assessment. The metrics are evaluated and analyzed to be applied as KPI’s to help MC companies prioritize efforts in business...
Applying Robust Design in an Industrial Context
DEFF Research Database (Denmark)
Christensen, Martin Ebro
mechanical architectures. Furthermore a set of 15 robust design principles for reducing the variation in functional performance is compiled in a format directly supporting the work of the design engineer. With these foundational methods in place, the existing tools, methods and KPIs of Robust Design...
The importance of robust design methodology
DEFF Research Database (Denmark)
Eifler, Tobias; Howard, Thomas J.
2018-01-01
infamous recalls in automotive history, that of the GM ignition switch, from the perspective of Robust Design. It is investigated if available Robust Design methods such as sensitivity analysis, tolerance stack-ups, design clarity, etc. would have been suitable to account for the performance variation...
Robust Control Charts for Time Series Data
Croux, C.; Gelper, S.; Mahieu, K.
2010-01-01
This article presents a control chart for time series data, based on the one-step- ahead forecast errors of the Holt-Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain
Efficient reanalysis techniques for robust topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Sigmund, Ole; Lazarov, Boyan Stefanov
2012-01-01
efficient robust topology optimization procedures based on reanalysis techniques. The approach is demonstrated on two compliant mechanism design problems where robust design is achieved by employing either a worst case formulation or a stochastic formulation. It is shown that the time spent on finite...
Extending the Scope of Robust Quadratic Optimization
Marandi, Ahmadreza; Ben-Tal, A.; den Hertog, Dick; Melenberg, Bertrand
In this paper, we derive tractable reformulations of the robust counterparts of convex quadratic and conic quadratic constraints with concave uncertainties for a broad range of uncertainty sets. For quadratic constraints with convex uncertainty, it is well-known that the robust counterpart is, in
Security and robustness for collaborative monitors
Testerink, Bas; Bulling, Nils; Dastani, Mehdi
2016-01-01
Decentralized monitors can be subject to robustness and security risks. Robustness risks include attacks on the monitor’s infrastructure in order to disable parts of its functionality. Security risks include attacks that try to extract information from the monitor and thereby possibly leak sensitive
Rumsey, Deborah
2011-01-01
The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.Tracks to a typical first semester statistics cou
Industrial statistics with Minitab
Cintas, Pere Grima; Llabres, Xavier Tort-Martorell
2012-01-01
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Explores
How Robust is Your System Resilience?
Homayounfar, M.; Muneepeerakul, R.
2017-12-01
Robustness and resilience are concepts in system thinking that have grown in importance and popularity. For many complex social-ecological systems, however, robustness and resilience are difficult to quantify and the connections and trade-offs between them difficult to study. Most studies have either focused on qualitative approaches to discuss their connections or considered only one of them under particular classes of disturbances. In this study, we present an analytical framework to address the linkage between robustness and resilience more systematically. Our analysis is based on a stylized dynamical model that operationalizes a widely used concept framework for social-ecological systems. The model enables us to rigorously define robustness and resilience and consequently investigate their connections. The results reveal the tradeoffs among performance, robustness, and resilience. They also show how the nature of the such tradeoffs varies with the choices of certain policies (e.g., taxation and investment in public infrastructure), internal stresses and external disturbances.
A Survey on Robustness in Railway Planning
DEFF Research Database (Denmark)
Lusby, Richard Martin; Larsen, Jesper; Bull, Simon Henry
2018-01-01
Planning problems in passenger railway range from long term strategic decision making to the detailed planning of operations.Operations research methods have played an increasing role in this planning process. However, recently more attention has been given to considerations of robustness...... in the quality of solutions to individual planning problems, and of operations in general. Robustness in general is the capacity for some system to absorb or resist changes. In the context of railway robustness it is often taken to be the capacity for operations to continue at some level when faced...... with a disruption such as delay or failure. This has resulted in more attention given to the inclusion of robustness measures and objectives in individual planning problems, and to the providing of tools to ensure operations continue under disrupted situations. In this paper we survey the literature on robustness...
Robust clustering of languages across Wikipedia growth
Ban, Kristina; Perc, Matjaž; Levnajić, Zoran
2017-10-01
Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.
Robust clustering of languages across Wikipedia growth
Ban, Kristina; Levnajić, Zoran
2017-01-01
Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy. PMID:29134106
Robust signatures of solar neutrino oscillation solutions
Bahcall, J N; Peña-Garay, C; Bahcall, John N.; Peña-Garay, Carlos
2002-01-01
With the goal of identifying signatures that select specific neutrino oscillation parameters, we test the robustness of global oscillation solutions that fit all the available solar and reactor experimental data. We use three global analysis strategies previously applied by different authors and also determine the sensitivity of the oscillation solutions to the critical nuclear fusion cross section, S_{17}(0), for the production of 8B. The neutral current to charged current ratio for SNO is predicted to be 3.5 +- 0.6 (1 sigma) for the favored LMA, LOW, and VAC solutions, which is separated from the no-oscillation value of 1.0 by much more than the expected experimental error. The predicted range of the day-night difference in charged current rates is between 0% and 21% (3 sigma) and is to be strongly correlated with the day-night effect for neutrino-electron scattering. A measurement by SNO of either a NC to CC ratio > 3.3 or a day-night difference > 10%, would favor a small region of the currently allowed LM...
50 CFR 600.410 - Collection and maintenance of statistics.
2010-10-01
... 50 Wildlife and Fisheries 8 2010-10-01 2010-10-01 false Collection and maintenance of statistics... of Statistics § 600.410 Collection and maintenance of statistics. (a) General. (1) All statistics..., the Assistant Administrator will remove all identifying particulars from the statistics if doing so is...
Recreational Boating Statistics 2012
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Recreational Boating Statistics 2013
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Statistical data analysis handbook
National Research Council Canada - National Science Library
Wall, Francis J
1986-01-01
It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics...
U.S. Department of Health & Human Services — The CMS Office of Enterprise Data and Analytics has developed CMS Program Statistics, which includes detailed summary statistics on national health care, Medicare...
Recreational Boating Statistics 2011
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
... Doing AMIGAS Stay Informed Cancer Home Uterine Cancer Statistics Language: English (US) Español (Spanish) Recommend on Facebook ... the most commonly diagnosed gynecologic cancer. U.S. Cancer Statistics Data Visualizations Tool The Data Visualizations tool makes ...
Tuberculosis Data and Statistics
... Advisory Groups Federal TB Task Force Data and Statistics Language: English (US) Español (Spanish) Recommend on Facebook ... Set) Mortality and Morbidity Weekly Reports Data and Statistics Decrease in Reported Tuberculosis Cases MMWR 2010; 59 ( ...
National transportation statistics 2011
2011-04-01
Compiled and published by the U.S. Department of Transportation's Bureau of Transportation Statistics : (BTS), National Transportation Statistics presents information on the U.S. transportation system, including : its physical components, safety reco...
National Transportation Statistics 2008
2009-01-08
Compiled and published by the U.S. Department of Transportations Bureau of Transportation Statistics (BTS), National Transportation Statistics presents information on the U.S. transportation system, including its physical components, safety record...
... News & Events About Us Home > Health Information Share Statistics Research shows that mental illnesses are common in ... of mental illnesses, such as suicide and disability. Statistics Top ı cs Mental Illness Any Anxiety Disorder ...