Appropriate for a one-semester course, this self-contained book is an introduction to nonparametric curve estimation theory. It may be used for teaching graduate students in statistics (in this case an intermediate statistical inference, on the level of the book by G. Casella and R. Berger (1990) "Statistical Inference," Brooks/Cole, is the prerequisite) as well as for diverse classes with students from other sciences including engineering, business, social, medical, and biology.
Appropriate for a one-semester course, this self-contained book is an introduction to nonparametric curve estimation theory. It may be used for teachi...
This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.
This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, f...