MultivariateTrimmedMean[matrix,f]
gives the mean of the bivariate data matrix after dropping a fraction f of the outermost vectors.
MultivariateTrimmedMean
MultivariateTrimmedMean[matrix,f]
gives the mean of the bivariate data matrix after dropping a fraction f of the outermost vectors.
更多信息和选项
- To use MultivariateTrimmedMean, you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
- MultivariateTrimmedMean gives a robust estimate of the mean by excluding extreme values.
- The outlying vectors are removed by repeatedly peeling off layers of convex hulls from the data until at least a fraction f have been removed.
- MultivariateTrimmedMean interpolates between the means of the points remaining before and after the last layer is removed.
- MultivariateTrimmedMean[matrix,0] is equivalent to Mean[matrix].
- MultivariateTrimmedMean[matrix,f] approaches ConvexHullMedian[matrix] as f approaches 1.
文本
Wolfram Research (2007),MultivariateTrimmedMean,Wolfram 语言函数,https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateTrimmedMean.html.
CMS
Wolfram 语言. 2007. "MultivariateTrimmedMean." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateTrimmedMean.html.
APA
Wolfram 语言. (2007). MultivariateTrimmedMean. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateTrimmedMean.html 年
BibTeX
@misc{reference.wolfram_2025_multivariatetrimmedmean, author="Wolfram Research", title="{MultivariateTrimmedMean}", year="2007", howpublished="\url{https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateTrimmedMean.html}", note=[Accessed: 01-May-2026]}
BibLaTeX
@online{reference.wolfram_2025_multivariatetrimmedmean, organization={Wolfram Research}, title={MultivariateTrimmedMean}, year={2007}, url={https://reference.wolfram.com/language/MultivariateStatistics/ref/MultivariateTrimmedMean.html}, note=[Accessed: 01-May-2026]}