Applied nonparametric regression

Wolfgang Karl Härdle

doi:10.5860/choice.29-0364

Abstract

Preface Part I. Regression Smoothing: 1. Introduction 2. Basic idea of smoothing 3. Smoothing techniques Part II. The Kernel Method: 4. How close is the smooth to the true curve? 5. Choosing the smoothing parameter 6. Data sets with outliers 7. Smoothing with correlated data 8. Looking for special features (qualitative smoothing) 9. Incorporating parametric components and alternatives Part III. Smoothing in High Dimensions: 10. Investigating multiple regression by additive models Appendices References List of symbols and notation.

Keywords

Nonparametric regressionNonparametric statisticsRegressionStatisticsRegression analysisMathematicsEconometricsComputer science

Affiliated Institutions

University of Bonn DE

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Publication Info

Year: 1991
Type: article
Volume: 29
Issue: 01
Pages: 29-0364
Citations: 2612
Access: Closed

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APA Style

                            
                                    Wolfgang Karl Härdle
                                
                            (1991). 
                            Applied nonparametric regression. 
                            Choice Reviews Online
                            , 29
                            (01)
                            , 29-0364.
                            https://doi.org/10.5860/choice.29-0364

Identifiers

DOI: 10.5860/choice.29-0364