Nonparametric and Semiparametric Models [Paperback]

1 Introduction.- 1.1 Density Estimation.- 1.2 Regression.- Summary.- I Nonparametric Models.- 2 Histogram.- 3 Nonparametric Density Estimation.- 4 Nonparametric Regression.- II Semiparametric Models.- 5 Semiparametric and Generalized Regression Models.- 6 Single Index Models.- 7 Generalized Partial Linear Models.- 8 Additive Models and Marginal Effects.- 9 Generalized Additive Models.- References.- Author Index.

From the reviews:

This book contains a good coverage of some of the widely used nonparametric and semiparametric modeling techniques. & The concepts are presented very clearly with numerous examples and data analytic illustrations. & Authors have done a good job of illustrating the concepts and the methodology with very well chosen examples. The exercises at the end of each chapter are carefully prepared so that students become familiar with the important issues. This book will be very useful for students in statistics, biostatistics and econometrics. (Probal Chaudhuri, Sankhya, Vol. 67 (1), 2005)

This is another book by Professor Wolfgang H?rdle and his colleagues on nonparametric statistics and smoothing. The unique feature of this book is the inclusion of topics on semi-parametric regression models for high-dimensional data. & Minimum theory and numerical examples are covered in this book, which makes this book mostly suitable for a course in nonparametric regression to graduate students. & will be useful for readers who would like to understand the statistical and mathematical principles and basic concepts and techniques of smoothing. (Dongsheng Tu, Zentralblatt MATH, Vol. 1059 (10), 2005)

This book deals with the problem of how to estimate & . As such the problems that it deals with are closely related to the exploratory data analysis techniques & . The text is well organized, with some exercises, which in the later sections of the book have the character of research tlÃ%