Generalized Additive Models

Regular price €94.99
A01=Simon N. Wood
advanced statistics course
AIC Comparison
applied regression analysis in R
Author_Simon N. Wood
Category=PBT
Ck Level
Co-variance Matrix
Cubic Spline
data smoothing techniques
Deviance Residuals
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Equal Fit
Gam
GCV Score
generalized linear models
GLR Testing
Large Sample Limit
likelihood inference
Linear Mixed Model
Linear Predictor
mgcv package
mixed models
Model Manifold
nonparametric regression
Ordinary Linear Model
penalised likelihood
Penalized Regression Spline
Penalty Matrix
Piecewise Linear
QR Decomposition
random effects
Regression Spline
Single Index Model
Smooth Terms
smoothing
Smoothing Parameter
Smoothing Parameter Estimation
Soap Film
splines
statistical modelling
Thin Plate Regression Spline

Product details

  • ISBN 9781498728331
  • Weight: 900g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 May 2017
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models.

The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study.

Simon N. Wood is a professor of Statistical Science at the University of Bristol, UK, and author of the R package mgcv.