Convergence of Conditional Metropolis-Hastings Samplers
نویسندگان
چکیده
منابع مشابه
Convergence of Conditional Metropolis-Hastings Samplers
We consider Markov chain Monte Carlo algorithms which combine Gibbs updates with Metropolis-Hastings updates, resulting in a conditional Metropolis-Hastings sampler (CMH). We develop conditions under which the CMH will be geometrically or uniformly ergodic. We illustrate our results by analysing a CMH used for drawing Bayesian inferences about the entire sample path of a diffusion process, base...
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ژورنال
عنوان ژورنال: Advances in Applied Probability
سال: 2014
ISSN: 0001-8678,1475-6064
DOI: 10.1239/aap/1401369701