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


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a254769.pdf


Report Date : 21 Jul 1992


Pagination or Media Count : 39


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