MultivariateMeanDeviation[matrix]
gives the mean of the Euclidean distances between the elements of matrix and their mean.
MultivariateMeanDeviation
MultivariateMeanDeviation[matrix]
gives the mean of the Euclidean distances between the elements of matrix and their mean.
更多信息和选项
- To use MultivariateMeanDeviation, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
- MultivariateMeanDeviation is a univariate measure of mean deviation for multivariate data.
- The multivariate mean deviation is given by
∑iNorm[xi-
], where matrix={x1,x2,…,xn} and
=Mean[matrix]. - MultivariateMeanDeviation handles both numerical and symbolic data.
文本
Wolfram Research (2007),MultivariateMeanDeviation,Wolfram 语言函数,https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html.
CMS
Wolfram 语言. 2007. "MultivariateMeanDeviation." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html.
APA
Wolfram 语言. (2007). MultivariateMeanDeviation. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html 年
BibTeX
@misc{reference.wolfram_2025_multivariatemeandeviation, author="Wolfram Research", title="{MultivariateMeanDeviation}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html}", note=[Accessed: 11-April-2026]}
BibLaTeX
@online{reference.wolfram_2025_multivariatemeandeviation, organization={Wolfram Research}, title={MultivariateMeanDeviation}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateMeanDeviation.html}, note=[Accessed: 11-April-2026]}