Filtered Kernel Density Estimation.

Abstract

A modification of the kernel estimator for density estimation is proposed which allows the incorporation of local information about the smoothness of the density. The estimator used a small set of local bandwidths rather than a single global one as in the standard kernel estimator. It uses a set of filtering functions which determines the extent of influence of the local bandwidths. Various versions of the idea are discussed. The estimator is shown to be consistent and is illustrated by comparison to the single bandwidth kernel estimator for the case in which the filter functions are derived from finite mixture models.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1994
Accession Number
ADA288293

Entities

People

  • Carey E. Priebe
  • David J. Marchette
  • George W. Rogers
  • Jeffrey L. Solka

Organizations

  • George Mason University

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Bandwidth
  • Data Analysis
  • Data Science
  • Databases
  • Discriminant Analysis
  • Estimators
  • Filtration
  • Information Science
  • Military Research
  • Probability
  • Probability Density Functions
  • Signal Processing
  • Standards
  • Statistical Algorithms
  • Statistical Analysis
  • Statistics

Readers

  • Statistical inference.