Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Uniformly most powerful unbiased test for conditional independence in
  Gaussian graphical model   Model selection for Gaussian concentration graph is based on multiple testing
of pairwise conditional independence. In practical applications partial
correlation tests are widely used. However it is not known whether partial
correlation test is uniformly most powerful for pairwise conditional
independence testing. This question is answered in the paper. Uniformly most
powerful unbiased test of Neymann structure is obtained. It turns out, that
this test can be reduced to usual partial correlation test. It implies that
partial correlation test is uniformly most powerful unbiased one.

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The categories of this paper are: atom-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
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The categories of this paper are: hep-lat
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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: nucl-ex
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The categories of this paper are: gr-qc
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The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ph
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The categories of this paper are: econ
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The categories of this paper are: acc-phys
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The categories of this paper are: adap-org
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The categories of this paper are: bayes-an
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The categories of this paper are: q-bio