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Semi— and nonparametric approaches to regression analysis

  • Ludwig Fahrmeir
  • Gerhard Tutz
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this chapter developments are given that lead beyond the framework of parametric models. Instead of assuming a functional form that specifies how explanatory variables determine dependent variables, the functional form is assumed to be in some way smooth, and the data are allowed to determine the appropriate functional form under weak restrictions.

Keywords

Loss Function Generalize Additive Model Smoothing Parameter Spline Smoothing Kernel Smoothing 
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 Science+Business Media New York 1994

Authors and Affiliations

  • Ludwig Fahrmeir
    • 1
  • Gerhard Tutz
    • 2
  1. 1.Seminar für StatistikUniversität MünchenMünchenGermany
  2. 2.Institut für Quantitative MethodenTechnische Universität BerlinBerlinGermany

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