Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Understanding predictive information criteria for Bayesian models   We review the Akaike, deviance, and Watanabe-Akaike information criteria from
a Bayesian perspective, where the goal is to estimate expected
out-of-sample-prediction error using a biascorrected adjustment of
within-sample error. We focus on the choices involved in setting up these
measures, and we compare them in three simple examples, one theoretical and two
applied. The contribution of this review is to put all these information
criteria into a Bayesian predictive context and to better understand, through
small examples, how these methods can apply in practice.

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The categories of this paper are: funct-an
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The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
19
The categories of this paper are: eess
6
The categories of this paper are: astro-ph
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th