MultivariateStatistics`
MultivariateStatistics`

MultivariateKurtosis

MultivariateKurtosis[matrix]

gives a multivariate kurtosis coefficient for matrix.

Details and Options

  • To use MultivariateKurtosis, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
  • MultivariateKurtosis is a univariate measure of kurtosis for multivariate data.
  • MultivariateKurtosis[matrix] is equivalent to where matrix={x1,x2,,xn}, Mean[matrix], and is the estimated population covariance matrix.
  • For a matrix with columns, a value of the multivariate kurtosis coefficient close to indicates approximate multinormality.

Examples

Basic Examples  (1)

Multivariate kurtosis for bivariate data:

Wolfram Research (2007), MultivariateKurtosis, Wolfram Language function, https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html.

Text

Wolfram Research (2007), MultivariateKurtosis, Wolfram Language function, https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html.

CMS

Wolfram Language. 2007. "MultivariateKurtosis." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html.

APA

Wolfram Language. (2007). MultivariateKurtosis. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html

BibTeX

@misc{reference.wolfram_2024_multivariatekurtosis, author="Wolfram Research", title="{MultivariateKurtosis}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html}", note=[Accessed: 25-July-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_multivariatekurtosis, organization={Wolfram Research}, title={MultivariateKurtosis}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateKurtosis.html}, note=[Accessed: 25-July-2024 ]}