Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Power-Conditional-Expected Priors: Using g-priors with Random Imaginary
  Data for Variable Selection   The Zellner's g-prior and its recent hierarchical extensions are the most
popular default prior choices in the Bayesian variable selection context. These
prior set-ups can be expressed power-priors with fixed set of imaginary data.
In this paper, we borrow ideas from the power-expected-posterior (PEP) priors
in order to introduce, under the g-prior approach, an extra hierarchical level
that accounts for the imaginary data uncertainty. For normal regression
variable selection problems, the resulting power-conditional-expected-posterior
(PCEP) prior is a conjugate normal-inverse gamma prior which provides a
consistent variable selection procedure and gives support to more parsimonious
models than the ones supported using the g-prior and the hyper-g prior for
finite samples. Detailed illustrations and comparisons of the variable
selection procedures using the proposed method, the g-prior and the hyper-g
prior are provided using both simulated and real data examples.

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The categories of this paper are: nucl-ex
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The categories of this paper are: mtrl-th
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The categories of this paper are: econ
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The categories of this paper are: nlin
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The categories of this paper are: chem-ph
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The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: ao-sci
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: q-bio
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The categories of this paper are: comp-gas
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The categories of this paper are: acc-phys