288 Pages
21 Color & 18 B/W Illustrations
by
Chapman & Hall
288 Pages
21 Color & 18 B/W Illustrations
by
Chapman & Hall
Also available as eBook on:
This book provides a concise account of four components of regression and smoothing methods: linear regression, generalized linear models, spline and kernel methods, and generalized linear mixed models. By bringing together parametric regression and nonparametric smoothing methods, the book emphasizes connections across methods, enabling readers to recognize common structures and to adapt... Read more
Preface 1 Linear regression 2 Generalized linear regression 3 Smoothing methods: Splines and kernels 4 Generalized linear mixed regression Bibliography Index
Biography
Zhiqiang Tan is a Distinguished Professor in the Department of Statistics, Rutgers University. His research and teaching interests include Monte Carlo methods, causal inference, statistical learning, and related areas. He is a Fellow of the American Statistical Association, a Fellow of the Institute of Mathematical Statistics, and an Elected Member of the International Statistical Institute.
