Wolfram Language & System 11.0 (2016)|Legacy Documentation

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represents zero mean matrix distribution with row covariance matrix Σrow, column covariance matrix Σcol, and degrees of freedom parameter ν.

represents matrix distribution with mean matrix μ.


  • The probability density for a matrix of dimensions in a matrix distribution is proportional to with an identity matrix of length .
  • MatrixTDistribution[Σrow,Σcol,ν] is the distribution of MatrixNormalDistribution[Σ,Σcol] with sampled from InverseWishartMatrixDistribution[ν+n-1,Σrow].
  • The covariance matrices Σrow and Σcol can be any symmetric positive definite matrices of real numbers of dimensions {n,n} and {m,m}, respectively. The degrees of freedom parameter ν can be any positive number, and the mean matrix μ can be any matrix of real numbers of dimensions {n,m}.
  • MatrixTDistribution can be used with such functions as RandomVariate and MatrixPropertyDistribution.
Introduced in 2015