Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Use of a Single Pseudo-Sample in Approximate Bayesian Computation   We analyze the computational efficiency of approximate Bayesian computation
(ABC), which approximates a likelihood function by drawing pseudo-samples from
the associated model. For the rejection sampling version of ABC, it is known
that multiple pseudo-samples cannot substantially increase (and can
substantially decrease) the efficiency of the algorithm as compared to
employing a high-variance estimate based on a single pseudo-sample. We show
that this conclusion also holds for a Markov chain Monte Carlo version of ABC,
implying that it is unnecessary to tune the number of pseudo-samples used in
ABC-MCMC. This conclusion is in contrast to particle MCMC methods, for which
increasing the number of particles can provide large gains in computational
efficiency.

23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph