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Nonparametric Regression

  • Wolfgang Härdle
  • Axel Werwatz
  • Marlene Müller
  • Stefan Sperlich
Part of the Springer Series in Statistics book series (SSS)

Abstract

An important question in many fields of science is the relationship between two variables, say X and Y. Regression analysis is concerned with the question of how Y (the dependent variable) can be explained by X (the independent or explanatory or regressor variable). This means a relation of the form
$$ Y = m(X) $$
, where m(●) is a function in the mathematical sense. In many cases theory does not put any restrictions on the form of m(●), i.e. theory does not say whether m(●) is linear, quadratic, increasing in X , etc.. Hence, it is up to empirical analysis to use data to find out more about m(●).

Keywords

Mean Square Error Nonparametric Regression Kernel Regression Bibliographic Note Engel Curve 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Wolfgang Härdle
    • 1
  • Axel Werwatz
    • 2
  • Marlene Müller
    • 3
  • Stefan Sperlich
    • 4
  1. 1.CASE — Center for Applied Statistics and Economics Wirtschaftswissenschaftliche FakultätHumboldt-Universität zu BerlinBerlinGermany
  2. 2.DIW BerlinBerlinGermany
  3. 3.Fraunhofer ITWMKaiserslauternGermany
  4. 4.Departamento de EconomíaUniversidad Carlos III de MadridGetafe (Madrid)Spain

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