Expansions for the multivariate chi-square distribution
Three classes of expansions for the distribution function of the [chi]k2(d, R)-distribution are given, where k denotes the dimension, d the degree of freedom, and R the "accompanying correlation matrix." The first class generalizes the orthogonal series with generalized Laguerre polynomials, originally given by Krishnamoorthy and Parthasarathy [12]. The second class contains always absolutely convergent representations of the distribution function by univariate chi-square distributions and the third class provides also the probabilities for any unbounded rectangular regions. In particular, simple formulas are given for the three-variate case including singular correlation matrices R, which simplify the computation of third order Bonferroni inequalities, e.g., for the tail probabilities of max{[chi]i21 <= i <= k} (k > 3).
Year of publication: |
1991
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Authors: | Royen, T. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 38.1991, 2, p. 213-232
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Publisher: |
Elsevier |
Keywords: | multivariate chi-square distribution multivariate gamma distribution multivariate Rayleigh distribution |
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