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Wilks's lambda distribution : ウィキペディア英語版
Wilks's lambda distribution

In statistics, Wilks's lambda distribution (named for Samuel S. Wilks), is a probability distribution used in multivariate hypothesis testing, especially with regard to the likelihood-ratio test and multivariate analysis of variance (MANOVA). It is a multivariate generalization of the univariate ''F''-distribution, generalizing the ''F''-distribution in the same way that the Hotelling's ''T''-squared distribution generalizes Student's ''t''-distribution.
Wilks's lambda distribution is related to two independent Wishart distributed variables, and is defined as follows,〔

given
:A \sim W_p(\Sigma, m) \qquad B \sim W_p(\Sigma, n)
independent and with m \ge p
:\lambda = \frac = \frac \sim \Lambda(p,m,n)
where ''p'' is the number of dimensions. In the context of likelihood-ratio tests ''m'' is typically the error degrees of freedom, and ''n'' is the hypothesis degrees of freedom, so that n+m is the total degrees of freedom.〔
The distribution can be related to a product of independent beta-distributed random variables
:u_i \sim B\left(\frac,\frac\right)
:\prod_^p u_i \sim \Lambda(p,m,n).
For large ''m'', Bartlett's approximation〔
〕 allows Wilks's lambda to be approximated with a chi-squared distribution
:\left(\frac-m\right)\log \Lambda(p,m,n) \sim \chi^2_.
== See also ==

* Chi-squared distribution
* ''F''-distribution
* Gamma distribution
* Hotelling's ''T''-squared distribution
* Student's ''t''-distribution
* Wishart distribution

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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