A Formula for the Tail Probability of a Multivariate Normal Distribution and Its Applications
An exact asymptotic formula for the tail probability of a multivariate normal distribution is derived. This formula is applied to establish two asymptotic results for the maximum deviation from the mean: the weak convergence to the Gumbel distribution of a normalized maximum deviation and the precise almost sure rate of growth of the maximum deviation. The latter result gives rise to a diagnostic tool for checking multivariate normality by a simple graph in the plane. Some simulation results are presented.
Year of publication: |
2002
|
---|---|
Authors: | Hüsler, Jürg ; Liu, Regina Y. ; Singh, Kesar |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 82.2002, 2, p. 422-430
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Publisher: |
Elsevier |
Keywords: | multivariate normal distribution tail probability Gumbel distribution maximum deviation growth rate sum of [chi]2 random variables |
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