Generalized Linear Mixed Models with Applications in Agriculture and Biology, Salinas Ru?z
Автор: Lewontin Richard C., Levins Richard Название: Biology Under the Influence: Dialectical Essays on Ecology, Agriculture, and Health ISBN: 1583671579 ISBN-13(EAN): 9781583671573 Издательство: Неизвестно Рейтинг: Цена: 26670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a critique of genetic determinism and reductionism within science while exploring a range of issues including the nature of science, biology, evolution, the environment, public health, and dialectics. This work brings together the essays of two prominent scientists who work to empower the public`s understanding of science and nature.
Автор: Lee, Youngjo (Seoul National University, South Korea) Nelder, John A. Pawitan, Yudi (Karolinska Institute, Stockholm, Sweden) Название: Generalized Linear Models with Random Effects ISBN: 1032096632 ISBN-13(EAN): 9781032096636 Издательство: Taylor&Francis Рейтинг: Цена: 50010.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical basis of the methodology, new developments in var
Автор: Madsen, Henrik Название: Introduction to General and Generalized Linear Models ISBN: 1420091557 ISBN-13(EAN): 9781420091557 Издательство: Taylor&Francis Рейтинг: Цена: 71450.00 T Наличие на складе: Нет в наличии.
Автор: McCullagh, P. Название: Generalized Linear Models ISBN: 0412317605 ISBN-13(EAN): 9780412317606 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dey, Dipak K. Название: Generalized Linear Models ISBN: 0824790340 ISBN-13(EAN): 9780824790349 Издательство: Taylor&Francis Рейтинг: Цена: 132710.00 T Наличие на складе: Нет в наличии.
Название: Nonparametric Regression and Generalized Linear Models ISBN: 0412300400 ISBN-13(EAN): 9780412300400 Издательство: Taylor&Francis Рейтинг: Цена: 183750.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Salinas Ru?z Название: Generalized Linear Mixed Models with Applications in Agriculture and Biology ISBN: 3031328027 ISBN-13(EAN): 9783031328022 Издательство: Springer Рейтинг: Цена: 37260.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This open access book offers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed. An alternative to analyse non-normal distributed response variables is the use of generalized linear models (GLM) to describe the response data with an exponential family distribution that perfectly fits the real response. Extending this idea to models with random effects allows the use of Generalized Linear Mixed Models (GLMMs). The use of these complex models was not computationally feasible until the recent past, when computational advances and improvements to statistical analysis programs allowed users to easily, quickly, and accurately apply GLMM to data sets. GLMMs have attracted considerable attention in recent years. The word "Generalized" refers to non-normal distributions for the response variable and the word "Mixed" refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, ASReml, among others, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate complex correlation structures and types of response variables.
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: 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.
Название: An Introduction to Generalized Linear Models, Third Edition ISBN: 1584889500 ISBN-13(EAN): 9781584889502 Издательство: Taylor&Francis Рейтинг: Цена: 47970.00 T Наличие на складе: Нет в наличии. Описание: Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.
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