Read Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics)

Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics)

Thomas W Yee

4.9/5 (18651 ratings)

Description:This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole.Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs.The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics). To get started finding Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: —

Format: PDF, EPUB & Kindle Edition

Publisher: —

Release: —

ISBN: 1493928171

Description: This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole.Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs.The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics). To get started finding Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Special Offer | $0.00

Special Offer! | $0.00

Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics)

Vector Generalized Linear and Additive Models: With an Implementation in R (Springer Series in Statistics)

More Books

Vector Generalized Linear and Additive Models

Vector Generalized Linear and Additive Models

Consistent Higher Order Accurate Time Discretization Methods for Inelastic Material Models

Consistent Higher Order Accurate Time Discretization Methods for Inelastic Material Models

Mathematical Foundations of Quantum Field Theory

Mathematical Foundations of Quantum Field Theory

Nonlinear Approaches in Engineering Applications 2

Nonlinear Approaches in Engineering Applications 2

Handbook Of Mechanical Stability In Engineering (In 3 Volumes)

Handbook Of Mechanical Stability In Engineering (In 3 Volumes)

Encyclopedia of Optimization

Encyclopedia of Optimization

Copulae in Mathematical and Quantitative Finance

Copulae in Mathematical and Quantitative Finance

A General Electromagnetic Theory of Electric Machines

A General Electromagnetic Theory of Electric Machines

Multicriteria Analysis

Multicriteria Analysis