Bayesian Analysis of Constrained Parameter and Truncated Data Problems
STANFORD UNIV CA DEPT OF STATISTICS
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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.
- Statistics and Probability