Extending the Linear Model with R 2nd Edition

Inspect Banking Institution For Expanding the Linear Model with R 2nd Edition

1. ISBN-10

   9781498720960
2. ISBN-13

   978-1498720960

3. Julian J. Faraway serves as a professor of statistics within the Division of Mathematical Sciences at the School of Tub. His study concentrates on the analysis of practical and category information with specific relevance to the modeling of human motion. He achieved a PhD in statistics from the School of California, Berkeley.

Ever since the release of the successful, highly recommended initial edition, R has significantly widened both in reputation and in the number of available packages. Expanding the Linear Model with R: Generalized Linear, Blended Outcomes and Nonparametric Regression Models, Second Edition utilizes the enhanced functionality now obtainable in R and extensively revises and presents numerous subjects.

Fresh to the Second Edition

• Expanded coverage of binary and binomial responses, including proportion responses, quasibinomial and beta regression, and practical matters concerning these models
• New sections on Poisson models with dispersion, zero inflated count models, linear discriminant analysis, and sandwich and robust estimation for generalized linear models (GLMs)
• Overhauled chapters on random impacts and repeated measures that mirror modifications in the lme4 package and current approaches to conducting hypothesis testing for the models using different methods
• Novel chapter on the Bayesian analysis of blended impact models that illustrates the use of STAN and presents the approximation methodology of INLA
• Revised chapter on generalized linear mixed models to reflect the much richer assortment of fitting software now available
• Updated coverage of splines and confidence bands in the chapter on nonparametric regression
• Fresh material on random forests for regression and classification
• Refashioned R code throughout, particularly the many plots using the ggplot2 package
• Revised and expanded exercises with solutions now included

Illustrates the Interplay of Theory and Practice

This book continues to encompass a variety of methodologies that expand from the linear regression model. It introduces three expansions to the linear framework: GLMs, mixed impact models, and nonparametric regression models. The book elucidates data analysis using real examples and incorporates all the R instructions necessary to replicate the analyses.