The book is addressed to both the theoretical and applied statistician. It can be used as an undergraduate text.

Autorentext
Wolfgang Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.

Zusammenfassung
A principal feature of smoothing, the averaging of data points in a prescribed neighborhood, is not really practicable in dimensions greater than three if we have just one hundred data points.

Inhalt
I. Density Smoothing.- 1. The Histogram.- 2. Kernel Density Estimation.- 3. Further Density Estimators.- 4. Bandwidth Selection in Practice.- II. Regression Smoothing.- 5. Nonparametric Regression.- 6. Bandwidth Selection.- 7. Simultaneous Error Bars.- Tables.- Solutions.- List of Used S Commands.- Symbols and Notation.- References.