Examples of Adaptive MCMC
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Abstract
We investigate the use of adaptive MCMC algorithms to automatically tune the Markov chain parameters during a run. Examples include the Adaptive Metropolis (AM) multivariate algorithm of Haario, Saksman, and Tamminen (2001), Metropolis-within-Gibbs algorithms for nonconjugate hierarchical models, regionally adjusted Metropolis algorithms, and logarithmic scalings. Computer simulations indicate that the algorithms perform very well compared to nonadaptive algorithms, even in high dimension.
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The record
- Venue
- Journal of Computational and Graphical Statistics
- Topic
- Markov Chains and Monte Carlo Methods
- Field
- Mathematics
- Canadian institutions
- —
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Keywords
- Markov chain Monte CarloMetropolis–Hastings algorithmGibbs samplingMarkov chainComputer scienceAlgorithmLogarithmDimension (graph theory)Multivariate statisticsMathematicsArtificial intelligenceMachine learningBayesian probability
- Has abstract in OpenAlex
- yes