BAYESIAN-ANALYSIS OF LINEAR AND NONLINEAR POPULATION-MODELS BY USING THE GIBBS SAMPLER

被引:0
|
作者
WAKEFIELD, JC
SMITH, AFM
RACINEPOON, A
GELFAND, AE
机构
[1] UNIV LONDON IMPERIAL COLL SCI TECHNOL & MED, DEPT MATH, HUXLEY BLDG, 180 QUEENS GATE, LONDON SW7 2BZ, ENGLAND
[2] CIBA GEIGY AG, CH-4002 BASEL, SWITZERLAND
[3] UNIV CONNECTICUT, STORRS, CT 06268 USA
关键词
BAYESIAN ANALYSIS; GIBBS SAMPLER; HIERARCHICAL MODELS; MEAN VARIANCE RELATIONSHIPS; NONLINEAR MODELS; POPULATION MODELS; POPULATION OUTLIERS;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A fully Bayesian analysis of linear and non-linear population models has previously been unavailable, as a consequence of the seeming impossibility of performing the necessary numerical integrations in the complex multiparameter structures that typically arise in such models. It is demonstrated that, for a variety of linear and non-linear population models, a fully Bayesian analysis can be implemented in a straightforward manner by using the Gibbs sampler. The approach is illustrated with examples involving challenging problems of outliers and mean-variance relationships in population modelling.
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页码:201 / 221
页数:21
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