Design of Experiments for Generalized Linear Models, Russell Kenneth G.
Автор: Russell Название: Design of Experiments for Generalized Linear Models ISBN: 1498773133 ISBN-13(EAN): 9781498773133 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level, and without any information on computation.
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: 181670.00 T 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: Kaufman Robert L. Название: Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata ISBN: 150636537X ISBN-13(EAN): 9781506365374 Издательство: Sage Publications Рейтинг: Цена: 120390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Vonesh Edward F. Название: Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS ISBN: 1642953261 ISBN-13(EAN): 9781642953268 Издательство: Неизвестно Рейтинг: Цена: 186310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: 48990.00 T Наличие на складе: Нет в наличии. 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: Legler Название: Generalized Linear Models & Correla ISBN: 1439885389 ISBN-13(EAN): 9781439885383 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: For advanced undergraduate or non-major graduate students in Advanced Statistical Modeling or Regression II and courses in Generalized Linear Models, Longitudinal Data Analysis, Correlated Data, Multilevel Models. Material on R at the end of each chapter. Solutions manual for qualified instructors.
Автор: Robert Gilchrist; Brian Francis; Joe Whittaker Название: Generalized Linear Models ISBN: 0387962247 ISBN-13(EAN): 9780387962245 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dobson, Annette J. (university Of Queensland, Herston, Australia) Barnett, Adrian (queensland University Of Technology, Kelvin Grove, Australia) Название: Introduction to generalized linear models, fourth edition ISBN: 1138741515 ISBN-13(EAN): 9781138741515 Издательство: Taylor&Francis Рейтинг: Цена: 38720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, and a Postface on good statistical practice.
Автор: Morris Название: Design of Experiments ISBN: 1138111783 ISBN-13(EAN): 9781138111783 Издательство: Taylor&Francis Рейтинг: Цена: 81650.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for understanding the statistical aspects of experimental design as a whole within the structure provided by general linear models, rather than as a collection of seemingly unrelated solutions to unique problems.
The core material can be found in the first thirteen chapters. These chapters cover a review of linear statistical models, completely randomized designs, randomized complete blocks designs, Latin squares, analysis of data from orthogonally blocked designs, balanced incomplete block designs, random block effects, split-plot designs, and two-level factorial experiments. The remainder of the text discusses factorial group screening experiments, regression model design, and an introduction to optimal design. To emphasize the practical value of design, most chapters contain a short example of a real-world experiment. Details of the calculations performed using R, along with an overview of the R commands, are provided in an appendix.
This text enables students to fully appreciate the fundamental concepts and techniques of experimental design as well as the real-world value of design. It gives them a profound understanding of how design selection affects the information obtained in an experiment.
Автор: Dunn Название: Generalized linear models with examples ISBN: 1441901175 ISBN-13(EAN): 9781441901170 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics.
Автор: Dobson Название: An Introduction to Generalized Linear Models ISBN: 113874168X ISBN-13(EAN): 9781138741683 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, and a Postface on good statistical practice.
Автор: Gill, Jefferson M. Torres Pacheco, Silvia Michelle Название: Generalized linear models ISBN: 1506387349 ISBN-13(EAN): 9781506387345 Издательство: Sage Publications Рейтинг: Цена: 39060.00 T Наличие на складе: Поставка под заказ. Описание: Explaining the theoretical underpinning of generalized linear models, this text enables researchers to decide how to select the best way to adapt their data for this type of analysis, with examples to illustrate the application of GLM.
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