As of Version 8, MultivariateTDistribution is part of the built-in Wolfram Language kernel.
represents the multivariate Student distribution with scale matrix Σ and degrees of freedom parameter m.
represents the multivariate Student distribution with location μ, scale matrix Σ, and m degrees of freedom.
- To use , you first need to load the Multivariate Statistics Package using Needs["MultivariateStatistics`"].
- The probability density for vector x in a multivariate t distribution is proportional to (1+(x-μ).Σ-1.(x-μ)/m)-(m+Length[Σ])/2.
- The scale matrix Σ can be any real‐valued symmetric positive definite matrix.
- With specified location μ, μ can be any vector of real numbers, and Σ can be any symmetric positive definite p×p matrix with p=Length[μ].
- The multivariate Student distribution characterizes the ratio of a multinormal to the covariance between the variates.
- can be used with such functions as Mean, CDF, and RandomReal.