Convergence Rates for the Mean Integrated Squared Errors of Some Nonparametric Density Estimators of Recursive delta-Function Type.

Abstract

For estimation of a probability density function f by an empirical function f sub n based on a sample of size n from f, a widely used measure of goodness is the mean integrated squared error. For the well known delta-function type of f sub n, we show that the asymptotic behavior of this measure is essentially unchanged if f sub n is replaced by a recursive version. Also, we characterize this asymptotic behavior under somewhat milder smoothness restrictions on f than previously considered in the literature, at the expense however of adding tail restrictions on f.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1979
Accession Number
ADA072133

Entities

People

  • E. P. Cheng
  • Robert Serfling

Organizations

  • Florida State University

Tags

DTIC Thesaurus Topics

  • Classification
  • Convergence
  • Data Science
  • Delta Functions
  • Estimators
  • Hierarchies
  • Inequalities
  • Information Science
  • Literature
  • Numbers
  • Observation
  • Probability
  • Probability Density Functions
  • Security
  • Statistics
  • Universities

Fields of Study

  • Mathematics

Readers

  • Plasma Physics / Magnetohydrodynamics
  • Regression Analysis.
  • Statistical inference.