3. Kernel Regression

  1. Michael G. Schimek
  1. Pascal Sarda and
  2. Philippe Vieu

Published Online: 30 JAN 2012

DOI: 10.1002/9781118150658.ch3

Smoothing and Regression: Approaches, Computation, and Application

Smoothing and Regression: Approaches, Computation, and Application

How to Cite

Sarda, P. and Vieu, P. (2000) Kernel Regression, in Smoothing and Regression: Approaches, Computation, and Application (ed M. G. Schimek), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118150658.ch3

Editor Information

  1. Karl-Franzens-University of Graz, Austria, and University of Vienna, Austria

Author Information

  1. Université Paul Sabatier, Toulouse, France

Publication History

  1. Published Online: 30 JAN 2012
  2. Published Print: 24 JUL 2000

ISBN Information

Print ISBN: 9780471179467

Online ISBN: 9781118150658

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Keywords:

  • kernel regression;
  • Nadaraya–Watson kernel regression estimate;
  • pointwise bias properties;
  • pointwise variance properties;
  • mean squared error

Summary

This chapter contains sections titled:

  • Introduction

  • The Nadaraya–Watson Kernel Regression Estimate

  • Pointwise Bias Properties of the Nadaraya–Watson Estimate

  • Pointwise Variance Properties of the Nadaraya–Watson Estimate

  • Trade-off Between Bias and Variance: The Mean Squared Error

  • Global Results: Mean Integrated Squared Error Properties

  • L∞ Convergence Properties of the Nadaraya–Watson Estimate

  • Complementary Bibliography