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Confidence Intervals in Generalized Regression Models, Uusipaikka, Esa


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Цена: 9798.00р.
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Автор: Uusipaikka, Esa
Название:  Confidence Intervals in Generalized Regression Models
ISBN: 9780367387082
Издательство: Taylor&Francis
Классификация:
ISBN-10: 0367387085
Обложка/Формат: Paperback
Страницы: 324
Вес: 0.60 кг.
Дата издания: 27.09.2019
Язык: English
Размер: 231 x 155 x 20
Читательская аудитория: Tertiary education (us: college)
Основная тема: Statistical Computing
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
Описание:

A Cohesive Approach to Regression Models

Confidence Intervals in Generalized Regression Models introduces a unified representation--the generalized regression model (GRM)--of various types of regression models. It also uses a likelihood-based approach for performing statistical inference from statistical evidence consisting of data and its statistical model.

Provides a Large Collection of Models

The book encompasses a number of different regression models, from very simple to more complex ones. It covers the general linear model (GLM), nonlinear regression model, generalized linear model (GLIM), logistic regression model, Poisson regression model, multinomial regression model, and Cox regression model. The author also explains methods of constructing confidence regions, profile likelihood-based confidence intervals, and likelihood ratio tests.

Uses Statistical Inference Package to Make Inferences on Real-Valued Parameter Functions

Offering software that helps with statistical analyses, this book focuses on producing statistical inferences for data modeled by GRMs. It contains numerical and graphical results while providing the code online.




Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata

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
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Цена: 18058.00 р.
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.

Generalized Additive Models: An Introduction with R

Автор: Wood, Simon
Название: Generalized Additive Models: An Introduction with R
ISBN: 1584884746 ISBN-13(EAN): 9781584884743
Издательство: Taylor&Francis
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Цена: 10717.00 р.
Наличие на складе: Поставка под заказ.

Описание: An Introduction to Generalized Additive Models with R provides readers with a thorough understanding of the theory and practical applications of GAMs to enable informed use of these very flexible tools and other advanced related models. The author's approach is based on a framework of penalized regression splines, and he provides a gentle introduction through motivating chapters on linear and generalized linear models. The author uses the freely available R software throughout to explain the underlying theory and illustrate the practicalities of linear, generalized linear, and generalized additive models. The text is accompanied by a supporting Web site that contains R code and the datasets used in the book.

Integral Equations with Difference Kernels on Finite Intervals

Автор: Lev A. Sakhnovich
Название: Integral Equations with Difference Kernels on Finite Intervals
ISBN: 3319307630 ISBN-13(EAN): 9783319307633
Издательство: Springer
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Цена: 11878.00 р.
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Описание: Applications of the obtained results to optimal synthesis, light scattering, diffraction, and hydrodynamics problems are discussed in this book, which also describes how the theory of operators with difference kernels is applied to stable processes and used to solve the famous M.

Integral Equations with Difference Kernels on Finite Intervals

Автор: Lev A. Sakhnovich
Название: Integral Equations with Difference Kernels on Finite Intervals
ISBN: 3319164880 ISBN-13(EAN): 9783319164885
Издательство: Springer
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Цена: 11878.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Applications of the obtained results to optimal synthesis, light scattering, diffraction, and hydrodynamics problems are discussed in this book, which also describes how the theory of operators with difference kernels is applied to stable processes and used to solve the famous M.

Applied Regression Analysis and Generalized Linear Models

Автор: Fox John
Название: Applied Regression Analysis and Generalized Linear Models
ISBN: 1452205663 ISBN-13(EAN): 9781452205663
Издательство: Sage Publications
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Цена: 25027.00 р.
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Описание: Providing a modern treatment of regression analysis, linear models and closely related methods, this book introduces students to one of the most useful and widely used statistical tools for social research.

Generalized linear models with examples

Автор: Dunn
Название: Generalized linear models with examples
ISBN: 1441901175 ISBN-13(EAN): 9781441901170
Издательство: Springer
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Цена: 15372.00 р.
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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.

Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS

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
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Цена: 27947.00 р.
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.

Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences

Автор: Edward E. Gbur, Walter W. Stroup, Kevin S. McCarter, Susan Durham, Linda J. Young, Mary Christman, Mark West, Matthew Kramer
Название: Analysis of Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences
ISBN: 0891181822 ISBN-13(EAN): 9780891181828
Издательство: Wiley
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Цена: 9338.00 р.
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Описание:

Generalized Linear Mixed Models in the Agricultural and Natural Resources Sciences provides readers with an understanding and appreciation for the design and analysis of mixed models for non-normally distributed data. It is the only publication of its kind directed specifically toward the agricultural and natural resources sciences audience. Readers will especially benefit from the numerous worked examples based on actual experimental data and the discussion of pitfalls associated with incorrect analyses.


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