Nonparametric and Semiparametric Models [Hardcover]

The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

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 techniqul³¥