MultivariateStatistics`
MultivariateStatistics`

MultivariateSkewness

MultivariateSkewness[matrix]

matrix の多変量歪度係数を返す．

詳細とオプション

  • MultivariateSkewnessを使うためには，まず多変量統計パッケージをロードしなくてはならない．それにはNeeds["MultivariateStatistics`"]を実行する必要がある．
  • MultivariateSkewnessは多変量データの二変量歪度測定である．
  • MultivariateSkewness[matrix]はと等価である．ここでmatrix={x1,x2,…,xn}，Mean[matrix]であり，は推定母共分散行列である．
  • 多変量歪度の値がゼロに近いときは，楕円対称を意味する．

例題

例  (1)

二変量データの多変量歪度：

Wolfram Research (2007), MultivariateSkewness, Wolfram言語関数， https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html.

テキスト

Wolfram Research (2007), MultivariateSkewness, Wolfram言語関数， https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html.

CMS

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

APA

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

BibTeX

@misc{reference.wolfram_2024_multivariateskewness, author="Wolfram Research", title="{MultivariateSkewness}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html}", note=[Accessed: 22-November-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_multivariateskewness, organization={Wolfram Research}, title={MultivariateSkewness}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateSkewness.html}, note=[Accessed: 22-November-2024 ]}