Multiple and Generalized Nonparametric Regression

by John Fox

Overview

This book builds on John Fox's previous volume in the QASS Series, Non Parametric Simple Regression. In this book, the reader learns how to estimate and plot smooth functions when there are multiple independent variables.

Product Details

ISBN-13:	9780761921899
Publisher:	SAGE Publications
Publication date:	05/01/2000
Series:	Quantitative Applications in the Social Sciences , #131
Edition description:	New Edition
Pages:	96
Product dimensions:	5.50(w) x 8.50(h) x 0.19(d)

About the Author

John Fox received a BA from the City College of New York and a Ph D from the University of Michigan, both in Sociology. He is Professor Emeritus of Sociology at Mc Master University in Hamilton, Ontario, Canada, where he was previously the Senator William Mc Master Professor of Social Statistics. Prior to coming to Mc Master, he was Professor of Sociology, Professor of Mathematics and Statistics, and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics, including \emph{Applied Regression Analysis and Generalized Linear Models, Third Edition} (Sage, 2016). He is an elected member of the R Foundation, an associate editor of the Journal of Statistical Software, a prior editor of R News and its successor the R Journal, and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.

Table of Contents

Local Polynomial Multiple Regression
Additive Regression Models
Projection-Pursuit Regression
Regression Trees
Generalized Nonparametric Regression
Concluding Remarks
Integrating Nonparametric Regression in Statistical Practice