Faraway Extending the Linear Model with R

Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition
2. Auflage 2016
ISBN: 978-1-4987-2099-1
Verlag: CRC Press
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 413 Seiten

Reihe: Chapman & Hall/CRC Texts in Statistical Science

This book surveys the techniques that grow from the regression model, and presents three extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models. The author's treatment is thoroughly modern and covers topics that include GLM diagnostics, generalized linear mixed models, trees, and even the use of neural networks in statistics. The new edition has been thoroughly revised to bring all the topics and R code up to date.

Zielgruppe

Researchers and graduate students in statistics.

Autoren/Hrsg.

Faraway, Julian J.

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Introduction. Binomial Data. Count Regression. Contingency Tables. Multinomial Data. Generalized Linear Models. Other GLMS. Random Effects. Repeated Measures and Longitudinal Data. Mixed Effect Models For Nonnormal Responses. Nonparametric Regression. Additive Models. Trees. Neural Networks. Appendices.

Über Autor(innen)

Julian J. Faraway is a professor of statistics at the University of Bath, UK.