Описание: Edward F. Vonesh's Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS is devoted to the analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or generalized nonlinear models. Written in a clear, easy-to-understand manner, it provides applied statisticians with the necessary theory, tools, and understanding to conduct complex analyses of continuous and/or discrete correlated data in a longitudinal or clustered data setting. Using numerous and complex examples, the book emphasizes real-world applications where the underlying model requires a nonlinear rather than linear formulation and compares and contrasts the various estimation techniques for both marginal and mixed-effects models. The SAS procedures MIXED, GENMOD, GLIMMIX, and NLMIXED as well as user-specified macros will be used extensively in these applications. In addition, the book provides detailed software code with most examples so that readers can begin applying the various techniques immediately.
Описание: Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects.
Автор: Heidi H. Andersen; Malene Hojbjerre; Dorte Sorense Название: Linear and Graphical Models ISBN: 0387945210 ISBN-13(EAN): 9780387945217 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Provides an account of graphical models for multivariate complex normal distributions. Beginning with an introduction to the multivariate complex normal distribution, the authors develop the marginal and conditional distributions of random vectors and matrices. Then they introduce complex MANOVA models and hypothesis testing for these models.
Автор: W. Hennevogl; Ludwig Fahrmeir; Gerhard Tutz Название: Multivariate Statistical Modelling Based on Generalized Linear Models ISBN: 1441929002 ISBN-13(EAN): 9781441929006 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Filipiak Katarzyna, Markiewicz Augustyn, Von Rosen Dietrich Название: Multivariate, Multilinear and Mixed Linear Models ISBN: 3030754936 ISBN-13(EAN): 9783030754938 Издательство: Springer Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- Holonomic gradient method for multivariate distribution theory (Akimichi Takemura).- From normality to skewed multivariate distributions: a personal view (Tхnu Kollo).- Multivariate moments in multivariate analysis (Jolanta Pielaszkiewicz and Dietrich von Rosen).- Regularized estimation of covariance structure through quadratic loss function (Defei Zhang, Xiangzhao Cui, Chun Li, Jine Zhao, Li Zeng, and Jianxin Pan).- Separable covariance structure identification for doubly multivariate data (Katarzyna Filipiak, Daniel Klein, and Monika Mokrzycka).- Estimation and testing of the covariance structure of doubly multivariate data (Katarzyna Filipiak and Daniel Klein).- Testing equality of mean vectors with block-circular and block compound-symmetric covariance matrices (Carlos A. Coelho).- Estimation and testing hypotheses in two-level and three-level multivariate data with block compound symmetric covariance structure (Arkadiusz Koziol, Anuradha Roy, Roman Zmyślony, Ivan Zezula, and Miguel Fonseca).- Testing of multivariate repeated measures data with block exchangeable covariance structure (Ivan Zezula, Daniel Klein, and Anuradha Roy).- On a simplified approach to estimation in experiments with orthogonal block structure (Radoslaw Kala).- A review of the linear sufficiency and linear prediction sufficiency in the linear model with new observations (Stephen J. Haslett, Jarkko Isotalo, Radoslaw Kala, Augustyn Markiewicz, and Simo Puntanen).- Linear mixed-effects model using penalized spline based on data transformation methods (Syed Ejaz Ahmed, Dursun Aydın and Ersin Yılmaz).- MMLM meetings - List of Publications.- Index.
Описание: This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models.
Описание: Edward Vonesh's Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS is devoted to the analysis of correlated response data using SAS, with special emphasis on applications that require the use of generalized linear models or generalized nonlinear models. Written in a clear, easy-to-understand manner, it provides applied statisticians with the necessary theory, tools, and understanding to conduct complex analyses of continuous and/or discrete correlated data in a longitudinal or clustered data setting. Using numerous and complex examples, the book emphasizes real-world applications where the underlying model requires a nonlinear rather than linear formulation and compares and contrasts the various estimation techniques for both marginal and mixed-effects models. The SAS procedures MIXED, GENMOD, GLIMMIX, and NLMIXED as well as user-specified macros will be used extensively in these applications. In addition, the book provides detailed software code with most examples so that readers can begin applying the various techniques immediately.
Автор: Lee, Youngjo Ronnegard, Lars Noh, Maengseok Название: Data analysis using hierarchical generalized linear models with r ISBN: 0367657929 ISBN-13(EAN): 9780367657925 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Поставка под заказ.
Описание: Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the field and, using data examples, illustrates how to
Автор: Sengupta Debasis, Jammalamadaka S. Rao Название: Linear Models and Regression with R: An Integrated Approach ISBN: 9811229287 ISBN-13(EAN): 9789811229282 Издательство: World Scientific Publishing Рейтинг: Цена: 14852.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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 Рейтинг: Цена: от 6763.00 р. Наличие на складе: Есть
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: Kim, Kevin Название: Univariate and Multivariate General Linear Models ISBN: 158488634X ISBN-13(EAN): 9781584886341 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Поставка под заказ.
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