Univariate and Multivariate General Linear Models, Kim, Kevin
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: Donald B. Percival, Andrew T. Walden Название: Spectral Analysis for Univariate Time Series ISBN: 1107028140 ISBN-13(EAN): 9781107028142 Издательство: Cambridge Academ Рейтинг: Цена: 14573.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Grissom, Robert J. Название: Effect Sizes for Research ISBN: 0415877695 ISBN-13(EAN): 9780415877695 Издательство: Taylor&Francis Рейтинг: Цена: 7348.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws.
Автор: Mohammad Ahsanullah Название: Characterizations of univariate continuous distributions. ISBN: 9462391386 ISBN-13(EAN): 9789462391383 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Johnson, N.L. Название: Continuous Univariate Distributions ISBN: 0471584959 ISBN-13(EAN): 9780471584957 Издательство: Wiley Рейтинг: Цена: 36424.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Johnson, N.L. Название: Continuous Univariate Distributions ISBN: 0471584940 ISBN-13(EAN): 9780471584940 Издательство: Wiley Рейтинг: Цена: 36424.00 р. Наличие на складе: Поставка под заказ.
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: 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: 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: 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.
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