On 'Fit the Short Curve' Principle for Smoothing Nonparametric Estimators,

Abstract

Let (X, Y) be a bivariate random vector with EY < oo. The nonparametric regression problem is to estimate the regression function r(x) = E(Y/X = x) (1) based on a random sample (Xi, Yi), i=l,..,n from (X, Y). The Nadaraya-Watson (NW), the Nearest Neighbor (NN), and the Optimal Quantile (OQ) kernel type estimators of r(x) defined in (2)-(4) depend on smoothing parameters h, k and p, respectively. The asymptotic optimal form of these smoothing parameters is known, see Coulomb (1977) and Mack (1981).

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007134

Entities

People

  • Andrzej S. Kozek
  • Eugene F. Schuster

Organizations

  • University of Texas at El Paso

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Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.