用特征函数检验多变量高斯性

Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics Pub Date : 1997-07-21 DOI:10.1109/HOST.1997.613563

A. Zoubir, C.L. Brown, B. Boashash

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引用次数: 3

摘要

对先前开发的基于特征函数的高斯检验方法进行了改进。因此，测试的能力得到了提高。然后将该测试扩展到多变量情况，使其能够应用于相关数据。蒙特卡罗模拟进行了比较功率与其他两个测试的多变量高斯性，令人鼓舞的结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Testing multivariate Gaussianity with the characteristic function

A modification to a previously developed characteristic function based Gaussianity test is proposed. The power of the test is consequently improved. This test is then extended to the multivariate case, allowing it to be applied to correlated data. Monte Carlo simulations are performed to compare power with two other tests for multivariate Gaussianity, with encouraging results.

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Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics

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