Accession Number:

ADA231080

Title:

Bayesian Analysis of Constrained Parameter and Truncated Data Problems

Descriptive Note:

Technical rept.

Corporate Author:

STANFORD UNIV CA DEPT OF STATISTICS

Personal Author(s):

Report Date:

1991-01-04

Pagination or Media Count:

34.0

Abstract:

Bayesian analysis of constrained parameter and truncated data problems is complicated by the seeming need for, typically multidimensional, numerical integrations over awkwardly defined regions. This paper illustrates how the Gibbs sampler approach to Bayesian calculation Gelfand and Smith, 1990 avoids these difficulties and leads to straightforwardly implemented procedures, even for apparently very complicated model forms.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE