Mickael Salabasis: UC AB, Postal: Analyssektionen, SE-117 88 Stockholm, Sweden
Abstract: The full Bayesian treatment of error component models typically relies on data augmentation to produce the required inference. Never stricly necessary a direct approach is always possible though not necessarily practical. The mechanics of direct sampling are outlined and a template for including model uncertainty is described. The needed tools, relying on various Markov chain Monte Carlo techniques, are developed and direct sampling, with and without effect selection, is illustrated.
23 pages, First version: September 17, 2004. Revised: February 16, 2005.
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