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Extending the Linear Model with R

Book

Extending the Linear Model with R

DOI link for Extending the Linear Model with R

Extending the Linear Model with R book

Generalized Linear, Mixed Effects and Nonparametric Regression Models

Extending the Linear Model with R

DOI link for Extending the Linear Model with R

Extending the Linear Model with R book

Generalized Linear, Mixed Effects and Nonparametric Regression Models
ByJulian J. Faraway
Edition 1st Edition
First Published 2005
eBook Published 20 December 2005
Pub. Location New York
Imprint Chapman and Hall/CRC
DOI https://doi.org/10.1201/b15416
Pages 312
eBook ISBN 9780429208959
Subjects Bioscience, Mathematics & Statistics
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Faraway, J.J. (2005). Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/b15416

ABSTRACT

Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which situations each one applies. Following in those fo

TABLE OF CONTENTS

chapter 1|24 pages

Introduction

chapter 2|30 pages

Binomial Data

chapter 3|14 pages

Count Regression

chapter 4|26 pages

Contingency Tables

chapter 5|18 pages

Multinomial Data

chapter 6|20 pages

Generalized Linear Models

chapter 7|18 pages

Other GLMs

chapter 8|32 pages

Random Effects

chapter 9|16 pages

Repeated Measures and Longitudinal Data

chapter 10|10 pages

Mixed Effect Models for Nonnormal Responses

chapter 11|20 pages

Nonparametric Regression

chapter 12|22 pages

Additive Models

chapter 13|16 pages

Trees

chapter 14|10 pages

Neural Networks

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