Accession Number : ADA117460

Title :   Quantiles, Parametric-Select Density Estimations, and Bi-Information Parameter Estimators.

Descriptive Note : Technical rept.,

Corporate Author : TEXAS A AND M UNIV COLLEGE STATION INST OF STATISTICS

Personal Author(s) : Parzen,Emanuel

PDF Url : ADA117460

Report Date : Jun 1982

Pagination or Media Count : 25

Abstract : This paper outlines a quantile-based approach to functional inference problems in which the parameters to be estimated are density functions. Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models. (Author)

Descriptors :   *Statistical inference, *Probability density functions, *Entropy, Parametric analysis, Estimates, Regression analysis, Sampling, Identification

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE