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A normality test for multivariate dependent samples
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DOI：10.1016/j.sigpro.2022.108705.png)
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Most normality tests in the literature are performed for scalar and independent samples. Thus, they be-come unreliable when applied to colored processes, hampering their use in realistic scenarios. We focus on Mardia's multivariate kurtosis, derive closed-form expressions of its asymptotic distribution for statis-tically dependent samples, under the null hypothesis of normality and a mixing condition. The calculus is long and tedious but the final result is simple and is implemented with a low computational burden. The proposed expression of the test exhibits good properties on various scenarios; this is illustrated by computer experiments by means of copulas.(c) 2022 Elsevier B.V. All rights reserved.
Keyword:
Multivariate normality test
Kurtosis
Colored process
Copula
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3.6
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被引数:
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