The Multivariate One Way Classification Model With Random Effects

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The Multivariate One-way Classification Model with Random Effects

Author : James Robert Schott
Publisher :
ISBN 13 :
Total Pages : 220 pages
Book Rating : 4.:/5 (87 download)

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Book Synopsis The Multivariate One-way Classification Model with Random Effects by : James Robert Schott

Download or read book The Multivariate One-way Classification Model with Random Effects written by James Robert Schott and published by . This book was released on 1981 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: A well-known model in univariate statistical analysis is the one-way random effects model. In this paper we investigate the multivariate generalization of this model, that is, the multivariate one-way random effects model. Two specific situations, regarding the structure of the variance-covariance matrix of the random error vectors, are considered. In the first and most general case, it is only assumed that this variance-covariance matrix is symmetric and positive definite. In the second case, it is assumed, in addition, that the variance-covariance matrix is a scalar multiple of the identity matrix. Maximum likelihood estimates are obtained and the likelihood ratio test for a hypothesis test on the rank of the variance-covariance matrix of the random effect vectors is derived. Properties of the likelihood ratio test are investigated for the general case, while for the second case an alternative test is developed and its properties are investigated. In each case a sequential procedure for determining the rank of the variance-covariance matrix of the random effect vectors is presented.

Multivariate One-way Classification Model with Random Effects

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (81 download)

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Book Synopsis Multivariate One-way Classification Model with Random Effects by :

Download or read book Multivariate One-way Classification Model with Random Effects written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Analysis of Variance for Random Models, Volume 2: Unbalanced Data

Author : Hardeo Sahai
Publisher : Springer Science & Business Media
ISBN 13 : 0817644253
Total Pages : 493 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis Analysis of Variance for Random Models, Volume 2: Unbalanced Data by : Hardeo Sahai

Download or read book Analysis of Variance for Random Models, Volume 2: Unbalanced Data written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2007-07-03 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs with a detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level. It also includes numerical examples to analyze data from a wide variety of disciplines as well as any worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example.

Applied Multivariate Analysis

Author : Neil H. Timm
Publisher : Springer Science & Business Media
ISBN 13 : 0387227717
Total Pages : 709 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Applied Multivariate Analysis by : Neil H. Timm

Download or read book Applied Multivariate Analysis written by Neil H. Timm and published by Springer Science & Business Media. This book was released on 2007-06-21 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a broad overview of the basic theory and methods of applied multivariate analysis. The presentation integrates both theory and practice including both the analysis of formal linear multivariate models and exploratory data analysis techniques. Each chapter contains the development of basic theoretical results with numerous applications illustrated using examples from the social and behavioral sciences, and other disciplines. All examples are analyzed using SAS for Windows Version 8.0.

Multivariate Analysis and Its Applications

Author : Theodore Wilbur Anderson
Publisher : IMS
ISBN 13 : 9780940600355
Total Pages : 502 pages
Book Rating : 4.6/5 (3 download)

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Book Synopsis Multivariate Analysis and Its Applications by : Theodore Wilbur Anderson

Download or read book Multivariate Analysis and Its Applications written by Theodore Wilbur Anderson and published by IMS. This book was released on 1994 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Multivariate Statistical Machine Learning Methods for Genomic Prediction

Author : Osval Antonio Montesinos López
Publisher : Springer Nature
ISBN 13 : 3030890104
Total Pages : 707 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Multivariate Statistical Machine Learning Methods for Genomic Prediction by : Osval Antonio Montesinos López

Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.

Hiroshima Mathematical Journal

Author :
Publisher :
ISBN 13 :
Total Pages : 572 pages
Book Rating : 4.:/5 (4 download)

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Book Synopsis Hiroshima Mathematical Journal by :

Download or read book Hiroshima Mathematical Journal written by and published by . This book was released on 1997 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Skew-Normal Model Theories and Their Applications

Author : Rendao Ye
Publisher : CRC Press
ISBN 13 : 1040155383
Total Pages : 273 pages
Book Rating : 4.0/5 (41 download)

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Book Synopsis Skew-Normal Model Theories and Their Applications by : Rendao Ye

Download or read book Skew-Normal Model Theories and Their Applications written by Rendao Ye and published by CRC Press. This book was released on 2024-11-08 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest. This book is of academic value as it helps to establish a series of statistical inference theories and methods for skew-normal mixed effects models. On the applications side, it provides efficient methods and tools for practical data analysis in various fields including economics, finance, biology and medical science.

Methods of Multivariate Analysis

Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470178965
Total Pages : 805 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Methods of Multivariate Analysis by : Alvin C. Rencher

Download or read book Methods of Multivariate Analysis written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2012-07-10 with total page 805 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere." —IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. This Third Edition continues to explore the key descriptive and inferential procedures that result from multivariate analysis. Following a brief overview of the topic, the book goes on to review the fundamentals of matrix algebra, sampling from multivariate populations, and the extension of common univariate statistical procedures (including t-tests, analysis of variance, and multiple regression) to analogous multivariate techniques that involve several dependent variables. The latter half of the book describes statistical tools that are uniquely multivariate in nature, including procedures for discriminating among groups, characterizing low-dimensional latent structure in high-dimensional data, identifying clusters in data, and graphically illustrating relationships in low-dimensional space. In addition, the authors explore a wealth of newly added topics, including: Confirmatory Factor Analysis Classification Trees Dynamic Graphics Transformations to Normality Prediction for Multivariate Multiple Regression Kronecker Products and Vec Notation New exercises have been added throughout the book, allowing readers to test their comprehension of the presented material. Detailed appendices provide partial solutions as well as supplemental tables, and an accompanying FTP site features the book's data sets and related SAS® code. Requiring only a basic background in statistics, Methods of Multivariate Analysis, Third Edition is an excellent book for courses on multivariate analysis and applied statistics at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for both statisticians and researchers across a wide variety of disciplines.

The Analysis of Variance

Author : Hardeo Sahai
Publisher : Springer Science & Business Media
ISBN 13 : 1461213444
Total Pages : 766 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis The Analysis of Variance by : Hardeo Sahai

Download or read book The Analysis of Variance written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 766 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

Statistical Tests for Mixed Linear Models

Author : André I. Khuri
Publisher : John Wiley & Sons
ISBN 13 : 1118164857
Total Pages : 384 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Statistical Tests for Mixed Linear Models by : André I. Khuri

Download or read book Statistical Tests for Mixed Linear Models written by André I. Khuri and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: An advanced discussion of linear models with mixed or randomeffects. In recent years a breakthrough has occurred in our ability todraw inferences from exact and optimum tests of variance componentmodels, generating much research activity that relies on linearmodels with mixed and random effects. This volume covers the mostimportant research of the past decade as well as the latestdevelopments in hypothesis testing. It compiles all currentlyavailable results in the area of exact and optimum tests forvariance component models and offers the only comprehensivetreatment for these models at an advanced level. Statistical Tests for Mixed Linear Models: Combines analysis and testing in one self-containedvolume. Describes analysis of variance (ANOVA) procedures in balancedand unbalanced data situations. Examines methods for determining the effect of imbalance ondata analysis. Explains exact and optimum tests and methods for theirderivation. Summarizes test procedures for multivariate mixed and randommodels. Enables novice readers to skip the derivations and discussionson optimum tests. Offers plentiful examples and exercises, manyof which are numerical in flavor. Provides solutions to selected exercises. Statistical Tests for Mixed Linear Models is an accessiblereference for researchers in analysis of variance, experimentaldesign, variance component analysis, and linear mixed models. It isalso an important text for graduate students interested in mixedmodels.

Bayesian Inference in Statistical Analysis

Author : George E. P. Box
Publisher : John Wiley & Sons
ISBN 13 : 111803144X
Total Pages : 610 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Bayesian Inference in Statistical Analysis by : George E. P. Box

Download or read book Bayesian Inference in Statistical Analysis written by George E. P. Box and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Its main objective is to examine the application and relevance of Bayes' theorem to problems that arise in scientific investigation in which inferences must be made regarding parameter values about which little is known a priori. Begins with a discussion of some important general aspects of the Bayesian approach such as the choice of prior distribution, particularly noninformative prior distribution, the problem of nuisance parameters and the role of sufficient statistics, followed by many standard problems concerned with the comparison of location and scale parameters. The main thrust is an investigation of questions with appropriate analysis of mathematical results which are illustrated with numerical examples, providing evidence of the value of the Bayesian approach.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

The Analysis of Variance

Author : Hardeo Sahai
Publisher : Springer Science & Business Media
ISBN 13 : 0817640126
Total Pages : 782 pages
Book Rating : 4.8/5 (176 download)

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Book Synopsis The Analysis of Variance by : Hardeo Sahai

Download or read book The Analysis of Variance written by Hardeo Sahai and published by Springer Science & Business Media. This book was released on 2000-01-27 with total page 782 pages. Available in PDF, EPUB and Kindle. Book excerpt: The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

Linear Models And Regression With R: An Integrated Approach

Author : Debasis Sengupta
Publisher : World Scientific
ISBN 13 : 9811200424
Total Pages : 773 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Linear Models And Regression With R: An Integrated Approach by : Debasis Sengupta

Download or read book Linear Models And Regression With R: An Integrated Approach written by Debasis Sengupta and published by World Scientific. This book was released on 2019-07-30 with total page 773 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed.The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references.This completely updated and new edition of Linear Models: An Integrated Approach includes the following features:

Advanced Linear Models

Author : Shein-Chung Chow
Publisher : Routledge
ISBN 13 : 1351468561
Total Pages : 552 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Advanced Linear Models by : Shein-Chung Chow

Download or read book Advanced Linear Models written by Shein-Chung Chow and published by Routledge. This book was released on 2018-05-04 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work details the statistical inference of linear models including parameter estimation, hypothesis testing, confidence intervals, and prediction. The authors discuss the application of statistical theories and methodologies to various linear models such as the linear regression model, the analysis of variance model, the analysis of covariance model, and the variance components model.

An Author and Permuted Title Index to Selected Statistical Journals

Author : Brian L. Joiner
Publisher :
ISBN 13 :
Total Pages : 512 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis An Author and Permuted Title Index to Selected Statistical Journals by : Brian L. Joiner

Download or read book An Author and Permuted Title Index to Selected Statistical Journals written by Brian L. Joiner and published by . This book was released on 1970 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: All articles, notes, queries, corrigenda, and obituaries appearing in the following journals during the indicated years are indexed: Annals of mathematical statistics, 1961-1969; Biometrics, 1965-1969#3; Biometrics, 1951-1969; Journal of the American Statistical Association, 1956-1969; Journal of the Royal Statistical Society, Series B, 1954-1969,#2; South African statistical journal, 1967-1969,#2; Technometrics, 1959-1969.--p.iv.