Goodness-of-Fit Tests for Bivariate and Multivariate Skew-Normal Distributions

被引：17

作者：

Meintanis, Simos G. ^{[2
]}

Hlavka, Zdenek ^{[1
]}

机构：

[1] Charles Univ Prague, Dept Stat, Prague, Czech Republic

[2] Natl & Kapodistrian Univ Athens, Dept Econ, Athens 10559, Greece

来源：

SCANDINAVIAN JOURNAL OF STATISTICS | 2010年 / 37卷 / 04期

关键词：

goodness-of-fit; moment-generating function; parametric bootstrap; skew-normal distribution; PARAMETERS;

D O I：

10.1111/j.1467-9469.2009.00687.x

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Goodness-of-fit tests are proposed for the skew-normal law in arbitrary dimension. In the bivariate case the proposed tests utilize the fact that the moment-generating function of the skew-normal variable is quite simple and satisfies a partial differential equation of the first order. This differential equation is estimated from the sample and the test statistic is constructed as an L-2-type distance measure incorporating this estimate. Extension of the procedure to dimension greater than two is suggested whereas an effective bootstrap procedure is used to study the behaviour of the new method with real and simulated data.

引用

页码：701 / 714

页数：14

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