Univariate and Multivariate General Linear Models, Kim, Kevin , Timm, Neil

Автор: Johnson, N.L.
Название: Continuous Univariate Distributions
ISBN: 0471584940 ISBN-13(EAN): 9780471584940
Издательство: Wiley
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Цена: 242830.00 T
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Описание: This volume presents a detailed description of the statistical distributions that are commonly applied to such fields as engineering, business, economics and the behavioural, biological and environmental sciences.

Автор: Johnson, N.L.
Название: Continuous Univariate Distributions
ISBN: 0471584959 ISBN-13(EAN): 9780471584957
Издательство: Wiley
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Цена: 242830.00 T
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Описание: This volume contains a detailed description of the statistical distributions that are commonly used in various applied areas, such as engineering, business, economics and the behavioural, biological and environmental sciences. It covers general and specific continuous distributions.

Автор: Robert J. Grissom, John J. Kim
Название: Effect Sizes for Research: Univariate and Multivariate Applications, Second Edition
ISBN: 0415877687 ISBN-13(EAN): 9780415877688
Издательство: Taylor&Francis
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Цена: 148010.00 T
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Описание: Noted for its comprehensive coverage, this greatly expanded new edition now covers the use of univariate and multivariate effect sizes. Many measures and estimators are reviewed along with their application, interpretation, and limitations. Noted for its practical approach, the book features numerous examples using real data for a variety of variables and designs, to help readers apply the material to their own data. Tips on the use of SPSS, SAS, R, and S-Plus are provided. The book's broad disciplinary appeal results from its inclusion of a variety of examples from psychology, medicine, education, and other social sciences. Special attention is paid to confidence intervals, the statistical assumptions of the methods, and robust estimators of effect sizes. The extensive reference section is appreciated by all. With more than 40% new material, highlights of the new editon include: three new multivariate chapters covering effect sizes for analysis of covariance, multiple regression/correlation, and multivariate analysis of variance more learning tools in each chapter including introductions, summaries, "Tips and Pitfalls" and more conceptual and computational questions more coverage of univariate effect sizes, confidence intervals, and effect sizes for repeated measures to reflect their increased use in research more software references for calculating effect sizes and their confidence intervals including SPSS, SAS, R, and S-Plus the data used in the book are now provided on the web along with new data and suggested calculations with IBM SPSS syntax for computational practice. Effect Sizes for Research covers standardized and unstandardized differences between means, correlational measures, strength of association, and parametric and nonparametric measures for between- and within-groups data. Intended as a resource for professionals, researchers, and advanced students in a variety of fields, this book is also an excellent supplement for advanced statistics courses in psychology, education, the social sciences, business, and medicine. A prerequisite of introductory statistics through factorial analysis of variance and chi-square is recommended.

Автор: Mohammad Ahsanullah
Название: Characterizations of univariate continuous distributions.
ISBN: 9462391386 ISBN-13(EAN): 9789462391383
Издательство: Springer
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Цена: 88500.00 T
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Описание: Provides in an organized manner characterizations of univariate probability distributions with many new results published in this area since the 1978 work of Golambos & Kotz "Characterizations of Probability Distributions" (Springer), together with applications of the theory in model fitting and predictions.

Автор: G.G. Hamedani
Название: Characterizations of Recently Introduced Univariate Continuous Distributions II
ISBN: 1536150959 ISBN-13(EAN): 9781536150957
Издательство: Nova Science
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Цена: 215410.00 T
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Описание: This monograph is, as far as the author has gathered, the second of its kind (the first one was published by Nova in 2017 with coauthors Hamedani and Maadooliat) which presents various characterizations of a wide variety of continuous distributions. These two monographs could also be used as sources to prevent reinventing and duplicating the already exiting distributions. The current book consists of seven chapters. The first chapter lists cumulative and density functions of two hundred and twenty univariate distributions. Chapter two provides characterizations of these distributions: (i) based on the ration of two truncated moments; (ii) in terms of the hazard function; (iii) in terms of the reverse hazard function; (iv) based on the conditional expectation of certain functions of the random variable. Chapter three includes the characterizations of twenty distributions, which appeared in a published paper (Hamedani and Safavimanesh, 2017). Chapter four presents characterizations of thirty six distributions, contains a published paper (Hamedani, 2017). Chapter five covers the characterizations of forty one distributions, which appeared in a published paper (Hamedani, 2018a). Chapter six presents characterizations of eighty distributions, contained in a published paper (Hamedani, 2018b). Finally, chapter seven consists of seventy proposed distributions. The main reason to include previously published papers in Chapters 3-6 is to provide a rather complete source for the interested researchers who would want to avoid reinventing the existing distributions.

Автор: Donald B. Percival, Andrew T. Walden
Название: Spectral Analysis for Univariate Time Series
ISBN: 1107028140 ISBN-13(EAN): 9781107028142
Издательство: Cambridge Academ
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Цена: 97150.00 T
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Описание: Spectral analysis is an important technique for interpreting time series data. This book uses the R language and real world examples to show data analysts interested in time series in the environmental, engineering and physical sciences how to bridge the gap between the statistical theory behind spectral analysis and its application to actual data.

Автор: Jammalamadaka S Rao, Sengupta Debasis
Название: Linear Models And Regression With R: An Integrated Approach
ISBN: 9811200408 ISBN-13(EAN): 9789811200403
Издательство: World Scientific Publishing
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Цена: 49600.00 T
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Описание:

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:

• Applications with data sets, and their implementation in R,
• Comprehensive coverage of regression diagnostics and model building,
• Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc.,
• Use of simple statistical ideas and interpretations to explain advanced concepts, and simpler proofs of many known results,
• Discussion of models covering mixed-effects/variance components, spatial, and time series data with partially unknown dispersion matrix,
• Thorough treatment of the singular linear model, including the case of multivariate response,
• Insight into updates in the linear model, and their connection with diagnostics, design, variable selection, Kalman filter, etc.,
• Extensive discussion of the foundations of linear inference, along with linear alternatives to least squares.
  

Автор: Whittaker, Joe
Название: Graphical models in applied multivariate statistics
ISBN: 0470743662 ISBN-13(EAN): 9780470743669
Издательство: Wiley
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Цена: 70700.00 T
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Описание: - It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included.

Автор: W. Hennevogl; Ludwig Fahrmeir; Gerhard Tutz
Название: Multivariate Statistical Modelling Based on Generalized Linear Models
ISBN: 1441929002 ISBN-13(EAN): 9781441929006
Издательство: Springer
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Цена: 181670.00 T
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Описание: The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.

Автор: V?ctor G?mez
Название: Multivariate Time Series With Linear State Space Structure
ISBN: 331928598X ISBN-13(EAN): 9783319285986
Издательство: Springer
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Цена: 88500.00 T
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Описание: This book presents a comprehensive study of multivariate time serieswith linear state space structure. The strength of the book also lies in the numerous algorithms includedfor state space models that take advantage of the recursive nature of themodels.