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Maximum Likelihood Estimates In The Multivariate Normal With Patterned Mean And Covariance Via The Em Algorithm
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Book Synopsis Maximum Likelihood Estimates in the Multivariate Normal with Patterned Mean and Covariance Via the Em Algorithm by : Dalton Francisco de Andrade
Download or read book Maximum Likelihood Estimates in the Multivariate Normal with Patterned Mean and Covariance Via the Em Algorithm written by Dalton Francisco de Andrade and published by . This book was released on 1983* with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Missing Data in the Multivariate Normal Patterned Mean and Covariance Matrix Testing and Estimation Problem by : Ted H. Szatrowski
Download or read book Missing Data in the Multivariate Normal Patterned Mean and Covariance Matrix Testing and Estimation Problem written by Ted H. Szatrowski and published by . This book was released on 1981 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating the Covariance Components of an Unbalanced Multivariate Latent Random Model Via the EM Algorithm by : Leonard Joseph Bianchi
Download or read book Estimating the Covariance Components of an Unbalanced Multivariate Latent Random Model Via the EM Algorithm written by Leonard Joseph Bianchi and published by . This book was released on 1987 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Analysis of Repeated Measures by : Martin J. Crowder
Download or read book Analysis of Repeated Measures written by Martin J. Crowder and published by Routledge. This book was released on 2017-10-24 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.
Book Synopsis The EM Algorithm for Maximum Likelihood Estimates of Multivariate Normal Parameters with Incomplete Data by : Richard A. Goodrum
Download or read book The EM Algorithm for Maximum Likelihood Estimates of Multivariate Normal Parameters with Incomplete Data written by Richard A. Goodrum and published by . This book was released on 1982 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Relative Efficiencies of Estimates Using Patterned Covariances Or Correlations in the Multivariate Normal Estimation Problem by : Ted H. Szatrowski
Download or read book Relative Efficiencies of Estimates Using Patterned Covariances Or Correlations in the Multivariate Normal Estimation Problem written by Ted H. Szatrowski and published by . This book was released on 1981 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Practical Longitudinal Data Analysis by : David J. Hand
Download or read book Practical Longitudinal Data Analysis written by David J. Hand and published by Routledge. This book was released on 2017-10-06 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.
Book Synopsis The EM Algorithm and Related Statistical Models by : Michiko Watanabe
Download or read book The EM Algorithm and Related Statistical Models written by Michiko Watanabe and published by CRC Press. This book was released on 2003-10-15 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including sta
Book Synopsis Variance Components by : Shayle R. Searle
Download or read book Variance Components written by Shayle R. Searle and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. ". . .Variance Components is an excellent book. It is organized and well written, and provides many references to a variety of topics. I recommend it to anyone with interest in linear models." —Journal of the American Statistical Association "This book provides a broad coverage of methods for estimating variance components which appeal to students and research workers . . . The authors make an outstanding contribution to teaching and research in the field of variance component estimation." —Mathematical Reviews "The authors have done an excellent job in collecting materials on a broad range of topics. Readers will indeed gain from using this book . . . I must say that the authors have done a commendable job in their scholarly presentation." —Technometrics This book focuses on summarizing the variability of statistical data known as the analysis of variance table. Penned in a readable style, it provides an up-to-date treatment of research in the area. The book begins with the history of analysis of variance and continues with discussions of balanced data, analysis of variance for unbalanced data, predictions of random variables, hierarchical models and Bayesian estimation, binary and discrete data, and the dispersion mean model.
Book Synopsis Finding MLE of Patterned Covariance Matrices by the EM Algorithm by : Donald B. Rubin
Download or read book Finding MLE of Patterned Covariance Matrices by the EM Algorithm written by Donald B. Rubin and published by . This book was released on 1981 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The EM Algorithm and Related Statistical Models by : Michiko Watanabe
Download or read book The EM Algorithm and Related Statistical Models written by Michiko Watanabe and published by CRC Press. This book was released on 2003-10-15 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring the application and formulation of the EM algorithm, The EM Algorithm and Related Statistical Models offers a valuable method for constructing statistical models when only incomplete information is available, and proposes specific estimation algorithms for solutions to incomplete data problems. The text covers current topics including statistical models with latent variables, as well as neural network models, and Markov Chain Monte Carlo methods. It describes software resources valuable for the processing of the EM algorithm with incomplete data and for general analysis of latent structure models of categorical data, and studies accelerated versions of the EM algorithm.
Book Synopsis The Handbook of Research Synthesis by : Harris Cooper
Download or read book The Handbook of Research Synthesis written by Harris Cooper and published by Russell Sage Foundation. This book was released on 1993-11-23 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: “The Handbook is a comprehensive treatment of literature synthesis and provides practical advice for anyone deep in the throes of, just teetering on the brink of, or attempting to decipher a meta-analysis. Given the expanding application and importance of literature synthesis, understanding both its strengths and weaknesses is essential for its practitioners and consumers. This volume is a good beginning for those who wish to gain that understanding.” —Chance “Meta-analysis, as the statistical analysis of a large collection of results from individual studies is called, has now achieved a status of respectability in medicine. This respectability, when combined with the slight hint of mystique that sometimes surrounds meta-analysis, ensures that results of studies that use it are treated with the respect they deserve....The Handbook of Research Synthesis is one of the most important publications in this subject both as a definitive reference book and a practical manual.”—British Medical Journal The Handbook of Research Synthesis is the definitive reference and how-to manual for behavioral and medical scientists applying the craft of research synthesis. It draws upon twenty years of ground-breaking advances that have transformed the practice of synthesizing research literature from an art into a scientific process in its own right. Editors Harris Cooper and Larry V. Hedges have brought together leading authorities to guide the reader through every stage of the research synthesis process—problem formulation, literature search and evaluation, statistical integration, and report preparation. The Handbook of Research Synthesis incorporates in a single volume state-of-the-art techniques from all quantitative synthesis traditions, including Bayesian inference and the meta-analytic approaches. Distilling a vast technical literature and many informal sources, the Handbook provides a portfolio of the most effective solutions to problems of quantitative data integration. The Handbook of Research Synthesis also provides a rich treatment of the non-statistical aspects of research synthesis. Topics include searching the literature, managing reference databases and registries, and developing coding schemes. Those engaged in research synthesis will also find useful advice on how tables, graphs, and narration can be deployed to provide the most meaningful communication of the results of research synthesis. The Handbook of Research Synthesis is an illuminating compilation of practical instruction, theory, and problem solving. It provides an accumulation of knowledge about the craft of reviewing a scientific literature that can be found in no other single source. The Handbook offers the reader thorough instruction in the skills necessary to conduct powerful research syntheses meeting the highest standards of objectivity, systematicity, and rigor demanded of scientific enquiry. This definitive work will represent the state of the art in research synthesis for years to come.
Book Synopsis The Oxford Handbook of Quantitative Methods in Psychology, Vol. 1 by : Todd D. Little
Download or read book The Oxford Handbook of Quantitative Methods in Psychology, Vol. 1 written by Todd D. Little and published by Oxford University Press. This book was released on 2013-03-21 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.
Book Synopsis Maximum Likelihood Estimation by : Scott R. Eliason
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE. This book was released on 1993 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.
Book Synopsis The SAGE Handbook of Quantitative Methods in Psychology by : Roger E Millsap
Download or read book The SAGE Handbook of Quantitative Methods in Psychology written by Roger E Millsap and published by SAGE. This book was released on 2009-07-23 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: `I often... wonder to myself whether the field needs another book, handbook, or encyclopedia on this topic. In this case I think that the answer is truly yes. The handbook is well focused on important issues in the field, and the chapters are written by recognized authorities in their fields. The book should appeal to anyone who wants an understanding of important topics that frequently go uncovered in graduate education in psychology′ - David C Howell, Professor Emeritus, University of Vermont Quantitative psychology is arguably one of the oldest disciplines within the field of psychology and nearly all psychologists are exposed to quantitative psychology in some form. While textbooks in statistics, research methods and psychological measurement exist, none offer a unified treatment of quantitative psychology. The SAGE Handbook of Quantitative Methods in Psychology does just that. Each chapter covers a methodological topic with equal attention paid to established theory and the challenges facing methodologists as they address new research questions using that particular methodology. The reader will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area. Drawing on a global scholarship, the Handbook is divided into seven parts: Part One: Design and Inference: addresses issues in the inference of causal relations from experimental and non-experimental research, along with the design of true experiments and quasi-experiments, and the problem of missing data due to various influences such as attrition or non-compliance. Part Two: Measurement Theory: begins with a chapter on classical test theory, followed by the common factor analysis model as a model for psychological measurement. The models for continuous latent variables in item-response theory are covered next, followed by a chapter on discrete latent variable models as represented in latent class analysis. Part Three: Scaling Methods: covers metric and non-metric scaling methods as developed in multidimensional scaling, followed by consideration of the scaling of discrete measures as found in dual scaling and correspondence analysis. Models for preference data such as those found in random utility theory are covered next. Part Four: Data Analysis: includes chapters on regression models, categorical data analysis, multilevel or hierarchical models, resampling methods, robust data analysis, meta-analysis, Bayesian data analysis, and cluster analysis. Part Five: Structural Equation Models: addresses topics in general structural equation modeling, nonlinear structural equation models, mixture models, and multilevel structural equation models. Part Six: Longitudinal Models: covers the analysis of longitudinal data via mixed modeling, time series analysis and event history analysis. Part Seven: Specialized Models: covers specific topics including the analysis of neuro-imaging data and functional data-analysis.
Book Synopsis Discriminant Analysis and Statistical Pattern Recognition by : Geoffrey J. McLachlan
Download or read book Discriminant Analysis and Statistical Pattern Recognition written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-25 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "For both applied and theoretical statisticians as well as investigators working in the many areas in which relevant use can be made of discriminant techniques, this monograph provides a modern, comprehensive, and systematic account of discriminant analysis, with the focus on the more recent advances in the field." –SciTech Book News ". . . a very useful source of information for any researcher working in discriminant analysis and pattern recognition." –Computational Statistics Discriminant Analysis and Statistical Pattern Recognition provides a systematic account of the subject. While the focus is on practical considerations, both theoretical and practical issues are explored. Among the advances covered are regularized discriminant analysis and bootstrap-based assessment of the performance of a sample-based discriminant rule, and extensions of discriminant analysis motivated by problems in statistical image analysis. The accompanying bibliography contains over 1,200 references.
Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb
Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by Newnes. This book was released on 1999 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an introduction to statistical pattern recognition theory and techniques. Most of the material presented in this book is concerned with discrimination and classification and has been drawn from a wide range of literature including that of engineering, statistics, computer science and the social sciences. This book is an attempt to provide a concise volume containing descriptions of many of the most useful of today's pattern processing techniques including many of the recent advances in nonparametric approaches to discrimination developed in the statistics literature and elsewhere. The techniques are illustrated with examples of real-world applications studies. Pointers are also provided to the diverse literature base where further details on applications, comparative studies and theoretical developments may be obtained"--Page [xv].
