Optimal Multiple Decision Statistical Procedure for Inverse Covariance Matrix

Alexander P. Koldanov () and Petr A. Koldanov ()
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Alexander P. Koldanov: National Research University, Higher School of Economics
Petr A. Koldanov: National Research University, Higher School of Economics

A chapter in Constructive Nonsmooth Analysis and Related Topics, 2014, pp 205-216 from Springer

Abstract: Abstract A multiple decision statistical problem for the elements of inverse covariance matrix is considered. Associated optimal unbiased multiple decision statistical procedure is given. This procedure is constructed using the Lehmann theory of multiple decision statistical procedures and the conditional tests of the Neyman structure. The equations for thresholds calculation for the tests of the Neyman structure are analyzed.

Keywords: Inverse covariance matrix; Tests of the Neyman structure; Multiple decision statistical procedure; Generating hypothesis (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4614-8615-2_13

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DOI: 10.1007/978-1-4614-8615-2_13

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