DISTRIBUTION OF THE LARGEST EIGENVALUE OF AN ELLIPTICAL WISHART MATRIX AND ITS SIMULATION

A. Shinozaki, Hiroki Hashiguchi, Toshiya Iwashita
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引用次数: 3

Abstract

This paper provides an alternative proof of the derivation of the distribution of the largest eigenvalue of an elliptical Wishart matrix in contrast to the result of CaroLopera et al. (2016). We show the relation between multivariate and matrix-variate t distributions. From this relation, we can generate random numbers drawn from the matrix-variate t distribution. A Monte Carlo simulation is conducted to evaluate the accuracy for the truncated distribution function of the largest eigenvalue of the elliptical Wishart matrix. Exact computation of the distribution of the smallest eigenvalue is also presented.
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椭圆wishart矩阵最大特征值的分布及其仿真
与CaroLopera等人(2016)的结果相比,本文提供了椭圆Wishart矩阵最大特征值分布的推导的另一种证明。我们展示了多元和矩阵变量t分布之间的关系。从这个关系中,我们可以从矩阵变量t分布中生成随机数。通过蒙特卡罗仿真,对椭圆型Wishart矩阵最大特征值截断分布函数的精度进行了评价。给出了最小特征值分布的精确计算。
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ENHANCING POWER OF SCORE TESTS FOR REGRESSION MODELS VIA FISHER TRANSFORMATION ANNOUNCEMENT: ON PUBLICATION OF THE JAPANESE JOURNAL OF STATISTICS AND DATA SCIENCE DISTRIBUTION OF THE LARGEST EIGENVALUE OF AN ELLIPTICAL WISHART MATRIX AND ITS SIMULATION COMMENT: ON CLOSING OF ENGLISH JOURNAL OF JSCS AND THE BIRTH OF NEW JOURNAL JJSD INFERENCE FOR THE EXTENT PARAMETER OF DAMAGE BY TSUNAMI WITH POINCARE CONES
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