Accession Number:

ADA254769

Title:

Bayesian Analysis of Linear and Nonlinear Population Models Using the Gibbs Sampler

Descriptive Note:

Technical rept.,

Corporate Author:

STANFORD UNIV CA DEPT OF STATISTICS

Personal Author(s):

• Wakefield, J. C.
• Smith, A. F.
• Racine-Poon, A.
• Gelfand, A. E.

Report Date:

1992-07-21

Pagination or Media Count:

39.0

Abstract:

A fully Bayesian analysis of linear and nonlinear population models has previously been unavailable, as a consequence of the seeming impossibility of performing the necessary numerical Integrations in the complex multi- parameter structures typically arising in such models. It is demonstrated that, for a variety of linear and nonlinear population models, a fully Bayesian analysis can be implemented in a straightforward manner using the Gibbs sampler. The approach is illustrated with examples involving challenging problems of outliers and mean-variance relationships in population modelling.

Descriptors:

• *STATISTICAL SAMPLES
• *BAYES THEOREM
• MODELS
• PARAMETERS
• INTEGRATION
• NONLINEAR ANALYSIS
• APPROACH
• SAMPLERS
• MEAN
• LINEARITY
• STRUCTURES
• POPULATION

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE