Wishart and Chi-Square Distributions Associated with Matrix Quadratic Forms

Thomas Mathew and Kenneth Nordström

Journal of Multivariate Analysis, 1997, vol. 61, issue 1, 129-143

Abstract: For a normally distributed random matrixYwith a general variance-covariance matrix[Sigma]Y, and for a nonnegative definite matrixQ, necessary and sufficient conditions are derived for the Wishartness ofY'QY. The conditions resemble those obtained by Wong, Masaro, and Wang (1991,J. Multivariate Anal.39, 154-174) and Wong and Wang (1993,J. Multivariate Anal.44, 146-159), but are verifiable and are obtained by elementary means. An explicit characterization is also obtained for the structure of[Sigma]Yunder which the distribution ofY'QYis Wishart. Assuming[Sigma]Ypositive definite, a necessary and sufficient condition is derived for every univariate quadratic fromlY'QYlto be distributed as a multiple of a chi-square. For the caseQ=In, the corresponding structure of[Sigma]Yis identified. An explicit counterexample is constructed showing that Wishartness ofY'Yneed not follow when, for every vectorl, l'Y'Ylis distributed as a multiple of a chi-square, complementing the well-known counterexample by Mitra (1969,Sankhya31, 19-22). Application of the results to multivariate components of variance models is briefly indicated.

Keywords: complex; covariance; structure; group; symmetry; covariance; model; multivariate; components; of; variance; model; skew-symmetric; matrix (search for similar items in EconPapers)
Date: 1997
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Citations: View citations in EconPapers (7)

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