The Amount of Noise Inherent in Bandwidth Selection for a Kernel Density Estimator.

Abstract

Any practical method of constructing a bandwidth must depend only on a statistical sample, and should produce some sort of estimate of this bandwidth. The purpose of this paper is to show that there a well-defined limits to the accuracy of all data-driven bandwidth estimates. Put another way, there is an unbridgeable gap between the minimum integrated square error attained using a optimal bandwidth and the minimum achievable integrated square error using a data-driven bandwidth estimate. Additional keywords: stochastic processes; cross validation; and random variables.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA160235

Entities

People

  • J. S. Marron
  • P. Hall

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Bandwidth
  • Classification
  • Data Science
  • Distribution Functions
  • Estimators
  • Information Science
  • North Carolina
  • Probability
  • Random Variables
  • Statistical Algorithms
  • Statistical Decision Theory
  • Statistical Estimation
  • Statistical Samples
  • Stochastic Processes
  • Theorems
  • Universities
  • Validation

Readers

  • Radio communications and signal processing.
  • Statistical inference.
  • Systems Analysis and Design