Implementing random scan Gibbs samplers
نویسندگان
چکیده
منابع مشابه
Implementing Random Scan Gibbs Samplers I
The Gibbs sampler, being a popular routine amongst Markov chain Monte Carlo sampling methodologies, has revolutionized the application of Monte Carlo methods in statistical computing practice. The performance of the Gibbs sampler relies heavily on the choice of sweep strategy, that is, the means by which the components or blocks of the random vector X of interest are visited and updated. We dev...
متن کاملComment: On Random Scan Gibbs Samplers
We congratulate the authors on a review of convergence rates for Gibbs sampling routines. Their combined work on studying convergence rates via orthogonal polynomials in the present paper under discussion (which we will denote as DKSC from here onward), via coupling in Diaconis, Khare and SaloffCoste (2006), and for multivariate samplers in Khare and Zhou (2008), enhances the toolbox of theoret...
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We consider two Bayesian hierarchical one-way random effects models and establish geometric ergodicity of the corresponding random scan Gibbs samplers. Geometric ergodicity, along with a moment condition, guarantees a central limit theorem for sample means and quantiles. In addition, it ensures the consistency of various methods for estimating the variance in the asymptotic normal distribution....
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We consider various versions of adaptive Gibbs and Metropoliswithin-Gibbs samplers, which update their selection probabilities (and perhaps also their proposal distributions) on the fly during a run, by learning as they go in an attempt to optimise the algorithm. We present a cautionary example of how even a simple-seeming adaptive Gibbs sampler may fail to converge. We then present various pos...
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If we wish to eeciently estimate the expectation of an arbitrary function on the basis of the output of a Gibbs sampler, which is better: deterministic or random sweep? In each case we calculate the asymptotic variance of the empirical estimator, the average of the function over the output, and determine the minimal asymptotic variance for estimators that use no information about the underlying...
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ژورنال
عنوان ژورنال: Computational Statistics
سال: 2005
ISSN: 0943-4062,1613-9658
DOI: 10.1007/bf02736129