Advertisement

Semiparametric and Generalized Regression Models

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

Abstract

In the previous part of this book we found the curse of dimensionality to be one of the major problems that arises when using nonparametric multivariate regression techniques. For the practitioner, a further problem is that for more than two regressors, graphical illustration or interpretation of the results is hardly ever possible. Truly multivariate regression models are often far too flexible and general for making detailed inference.

Keywords

Generalize Linear Model Link Function Generalize Additive Model Nonparametric Regression Exponential Family 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

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

Personalised recommendations