Accession Number:

AD0653272

Title:

NONPARAMETRIC ESTIMATION IN MARKOV PROCESSES.

Descriptive Note:

Technical rept.,

Corporate Author:

WISCONSIN UNIV MADISON DEPT OF STATISTICS

Personal Author(s):

Report Date:

1967-04-01

Pagination or Media Count:

13.0

Abstract:

The purpose of the present paper is to consider the non-parametric estimation of densities in the case of Markov processes. Asymptotically unbiased estimates for the initial and two-dimensional joint densities are constructed. These estimates are shown to be consistent in quadratic mean, and furthermore a consistent, in the probability sense, estimate for the transition density is obtained. It is shown that, under suitable conditions, all three estimators mentioned, properly normalized, are asymptotically normal.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE