On Jackknifing Kernel Regression Function Estimators.

Abstract

Estimation of the value of a regression function at a point of continuity using a kernal-type estimator is discussed and improvements of the technique by a generalized jackknife estimator are presented. It is shown that the generalized jackknife technique produces estimators with faster bias rates. In a small example it is investigated, if the generalized jackknife method works for all choices of bandwidths. It turns out that an improper choice of this parameter may inflate the mean square error of the generalized jackknife estimator. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA133236

Entities

People

  • Wolfgang Hardle

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Bandwidth
  • Classification
  • Computations
  • Contracts
  • Data Analysis
  • Data Science
  • Estimators
  • Information Science
  • Kernel Functions
  • North Carolina
  • Probability
  • Probability Density Functions
  • Random Variables
  • Security
  • Sequences
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.