Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Pseudo-Marginal Slice Sampling   Markov chain Monte Carlo (MCMC) methods asymptotically sample from complex
probability distributions. The pseudo-marginal MCMC framework only requires an
unbiased estimator of the unnormalized probability distribution function to
construct a Markov chain. However, the resulting chains are harder to tune to a
target distribution than conventional MCMC, and the types of updates available
are limited. We describe a general way to clamp and update the random numbers
used in a pseudo-marginal method's unbiased estimator. In this framework we can
use slice sampling and other adaptive methods. We obtain more robust Markov
chains, which often mix more quickly.

23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
1
The categories of this paper are: cs
28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
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The categories of this paper are: bayes-an
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The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con