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Generalized Linear Mixed Models with Applications in Agriculture and Biology, Salinas Ru?z


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Цена: 37260.00T
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Автор: Salinas Ru?z
Название:  Generalized Linear Mixed Models with Applications in Agriculture and Biology
ISBN: 9783031328022
Издательство: Springer
Классификация:


ISBN-10: 3031328027
Обложка/Формат: Soft cover
Страницы: 427
Вес: 0.00 кг.
Дата издания: 31.08.2023
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 5 illustrations, color; 43 illustrations, black and white; xiii, 427 p. 48 illus., 5 illus. in color.
Размер: 235 x 155
Основная тема: Life Sciences
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
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.
Дополнительное описание: Chapter 1) Elements of the Generalized Linear Mixed Models.- Chapter 2) Generalized Linear Models.- Chapter 3) Objectives in Model Inference.- Chapter 4) Generalized Linear Mixed Models for non-normal responses.- Chapter 5) Generalized Linear Mixed Models


Biology Under the Influence: Dialectical Essays on Ecology, Agriculture, and Health

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.

An Introduction to Generalized Linear Models, Third Edition

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.

Data analysis using hierarchical generalized linear models with r

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

Generalized Linear Models

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.

Generalized Linear Models

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.

Introduction to General and Generalized Linear Models

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.

Generalized Linear Models

Название: Generalized Linear Models
ISBN: 0367398605 ISBN-13(EAN): 9780367398606
Издательство: Taylor&Francis
Рейтинг:
Цена: 65320.00 T
Наличие на складе: Невозможна поставка.
Описание: This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.

Design of Experiments for Generalized Linear Models

Автор: Russell Kenneth G.
Название: Design of Experiments for Generalized Linear Models
ISBN: 1032094052 ISBN-13(EAN): 9781032094052
Издательство: Taylor&Francis
Рейтинг:
Цена: 42870.00 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.

Generalized Linear Models for Categorical and Continuous Limited Dependent Variables

Автор: Smithson, Michael
Название: Generalized Linear Models for Categorical and Continuous Limited Dependent Variables
ISBN: 1032477466 ISBN-13(EAN): 9781032477466
Издательство: Taylor&Francis
Рейтинг:
Цена: 47970.00 T
Наличие на складе: Нет в наличии.

Название: Count Time Series
ISBN: 1482248050 ISBN-13(EAN): 9781482248050
Издательство: Taylor&Francis
Рейтинг:
Цена: 78590.00 T
Наличие на складе: Книга еще не издана. Можно оформить предварительный заказ.

Generalized Linear Models with Random Effects

Название: Generalized Linear Models with Random Effects
ISBN: 1498720617 ISBN-13(EAN): 9781498720618
Издательство: Taylor&Francis
Рейтинг:
Цена: 117390.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Generalized Linear Mixed Models with Applications in Agriculture and Biology

Автор: Salinas Ru?z
Название: Generalized Linear Mixed Models with Applications in Agriculture and Biology
ISBN: 3031327993 ISBN-13(EAN): 9783031327995
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.


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