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Abstract

In the previous chapter, we discussed nonparametric density estimation. In this chapter, we discuss nonparametric estimation of the regression function E(yx) ≡ r(x), where y = r(x) + u and E(ux) = 0. More generally, we can consider functionals of the conditional distribution F y x , such as ∂r(x)/∂x and V(yx). But usually, estimation methods for the functionals can be inferred from those for E(yx).

Keywords

Asymptotic Distribution Near Neighbor Kernel Method Nonparametric Regression Kernel Estimator 
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 1996

Authors and Affiliations

  • Myoung-jae Lee
    • 1
  1. 1.Department of EconometricsTilburg UniversityTilburgThe Netherlands

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