Comparison of Methods for the Computation of Multivariate <I>t</I> Probabilities
比较了接受-拒绝、球-径向变换和变量分离变换等数值方法计算多元t概率的效率，发现基于Genz变换的方法最快，可处理多达20个变量的问题。
This article compares methods for the numerical computation of multivariate t probabilities for hyper-rectangular integration regions. Methods based on acceptance-rejection, spherical-radial transformations, and separation-of-variables transformations are considered. Tests using randomly chosen problems show that the most efficient numerical methods use a transformation developed by Genz for multivariate normal probabilities. These methods allow moderately accurate multivariate t probabilities to be quickly computed for problems with as many as 20 variables. Methods for the noncentral multivariate t distribution are also described.