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Optimal Multiple Decision Statistical Procedure for Inverse Covariance Matrix

In: Constructive Nonsmooth Analysis and Related Topics

Author

Listed:
  • Alexander P. Koldanov

    (National Research University, Higher School of Economics)

  • Petr A. Koldanov

    (National Research University, Higher School of Economics)

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.

Suggested Citation

  • Alexander P. Koldanov & Petr A. Koldanov, 2014. "Optimal Multiple Decision Statistical Procedure for Inverse Covariance Matrix," Springer Optimization and Its Applications, in: Vladimir F. Demyanov & Panos M. Pardalos & Mikhail Batsyn (ed.), Constructive Nonsmooth Analysis and Related Topics, edition 127, pages 205-216, Springer.
    • Handle: RePEc:spr:spochp:978-1-4614-8615-2_13
    DOI: 10.1007/978-1-4614-8615-2_13
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