NON-PARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION

Abstract

Given that a distribution function is a member of a subclass of absolutely continuous measures, the problem of nonparametric estimation is considered, with the method of maximum likelihood, of the underlying density function of a given sample of independent identically distributed random variables. Sufficient conditions on the space of probability densities and its topology are given for the consistency of such an estimate.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1963
Accession Number
AD0439259

Entities

People

  • G. B. Crawford
  • S. C. Saunders

Organizations

  • Boeing

Tags

DTIC Thesaurus Topics

  • Consistency
  • Continuity
  • Convergence
  • Discontinuities
  • Distribution Functions
  • Government Procurement
  • Governments
  • Mathematics
  • Maximum Likelihood Estimation
  • Probability
  • Random Variables
  • Scientific Research
  • Sequences
  • Theorems
  • Topology

Fields of Study

  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Regression Analysis.

Technology Areas

  • Space