represents the multivariate Student distribution with scale matrix Σ and degrees of freedom parameter ν.

represents the multivariate Student distribution with location μ, scale matrix Σ, and ν degrees of freedom.


  • The probability density for vector in a multivariate distribution is proportional to , where is the length of .
  • The multivariate Student distribution characterizes the ratio of a multinormal to the covariance between the variates.
  • MultivariateTDistribution allows Σ to be any × symmetric positive definite matrix, μ any vector of real numbers where p=Length[μ], and ν any positive real number.
  • MultivariateTDistribution can be used with such functions as Mean, CDF, and RandomVariate.
Introduced in 2010
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