ESTIMATION OF PROBABILITY DENSITY AND DISTRIBUTION FUNCTIONS.

Abstract

First and second order stochastic gradient algorithms are developed for suitably approximating the unknown density and distribution functions of a random vector, from a sequence of independent samples. Mean square error criterion and the integral square error criterion are used in the approximations. The rates of convergence and the approximation error are also evaluated. (Author)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1967
Accession Number
AD0660690

Entities

People

  • C. C. Blaydon
  • R. L. Kashyap

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Distribution Functions
  • Integrals
  • Mathematics
  • Probability

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Regression Analysis.