Abstract
In a first stage the authors show how the exact distribution of the likelihood ratio statistic used to test the reality of a covariance matrix may be expressed as the distribution of the sum of two independent random variables, one with a Generalized Integer Gamma distribution and the other with the distribution of a sum of independent Logbeta random variables. From this form of the exact distribution the authors develop then a family of near-exact distributions, based on finite mixtures of Generalized Near-Integer Gamma distributions. These near-exact distributions match, by construction, some of the first exact moments and they have very manageable cumulative distribution functions, which allow for an easy computation of sharp near-exact quantiles and p-values.
Original language | Unknown |
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Title of host publication | AIP Conference Proceedings |
Pages | 797-800 |
Volume | 1558 |
DOIs | |
Publication status | Published - 1 Jan 2013 |
Event | ICNAAM 2013: 11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS - Duration: 1 Jan 2013 → … |
Conference
Conference | ICNAAM 2013: 11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS |
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Period | 1/01/13 → … |