Applied Nonparametric Regression

Bibliographic Data

ID9726571
AuthorsPeter M Robinson (0000-0002-8516-9758), Wolfgang Haerdle
Year1991
Volume58
Issue232
Pages538
Publication date1991-11-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueEconomica (JOURNAL)
Journal identifiersISSN: 0013-0427 • E-ISSN: 1468-0335
PublisherJSTOR (PUBLISHER)
DOI10.2307/2554701
OpenAlexW2796632682
LanguageEN
Citations received3

Applied Nonparametric Regression is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable. The computer and the development of interactive graphics programs have made curve estimation possible. This volume focuses on the applications and practical problems of two central aspects of curve smoothing: the choice of smoothing parameters and the construction of confidence bounds. HA¤rdle argues that all smoothing methods are based on a local averaging mechanism and can be seen as essentially equivalent to kernel smoothing. To simplify the exposition, kernel smoothers are introduced and discussed in great detail. Building on this exposition, various other smoothing methods (among them splines and orthogonal polynomials) are presented and their merits discussed. All the methods presented can be understood on an intuitive level; however, exercises and supplemental materials are provided for those readers desiring a deeper understanding of the techniques. The methods covered in this text have numerous applications in many areas using statistical analysis. Examples are drawn from economics as well as from other disciplines including medicine and engineering

Cross-sectional regression · Econometrics · Economics · Nonparametric regression · Nonparametric statistics · Polynomial regression · Regression · Regression analysis · Statistics · Advanced Statistical Methods and Models · Mathematics · Statistical and Computational Modeling

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