Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive Independent Metropolis-Hastings by Fast Estimation of Mixtures
  of Normals   We construct an adaptive independent Metropolis-Hastings sampler that uses a
mixture of normals as a proposal distribution. To take full advantage of the
potential of adaptive sampling our algorithm updates the mixture of normals
frequently, starting early in the chain. The algorithm is built for speed and
reliability and its sampling performance is evaluated with real and simulated
examples. Our article outlines conditions for adaptive sampling to hold and
gives a readily accessible proof that under these conditions the sampling
scheme generates iterates that converge to the target distribution.

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The categories of this paper are: q-fin
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
1
The categories of this paper are: cs
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
21
The categories of this paper are: adap-org