I want to generate a random sample from a multivariate Cauchy distribution, however I couldn't find a function for the multivariate Cauchy in Mathematica. I know how to define a distribution in 1D and tried to do this in a similar way

MultivariateCauchy[x_, μ_, Σ_, k_] := Gamma[(1 + k)/2]/(Gamma[1/2] π^(k/2) Sqrt[Det[Σ]] 
     (1 +(Transpose[x -μ].Inverse[Σ].(x -μ))^((1 + k)/2)))

MCdist[μ_, Σ_, k_] := ProbabilityDistribution[MultivariateCauchy[x, μ, Σ, k], {x, -∞, ∞}]

where $\mu$ is the location vector, $\Sigma$ a positive definite covariance matrix and a free scalar parameter $k$. However, this does not work with RandomVariate. Is there a way to do this?

  • $\begingroup$ Why not use MultivariateTDistribution with v = 1? $\endgroup$
    – Andy Ross
    Mar 16, 2015 at 22:35

1 Answer 1


RandomVariate is only implemented for certain distributions and frequently fails for custom probability distributions.

Perhaps, this might be helpful (noting multivariate T is multi-Cauchy) but I am happy to delete if my post is wrong or ill-conceived.

fun[s_, k_, a_, b_] := 
 CopulaDistribution[{"MultivariateT", s, 
   k}, {CauchyDistribution[a, b], CauchyDistribution[a, b]}]

An example:

dist2 = fun[{{1, 0.7}, {0.7, 1}}, 1, 1, 1]


Quiet@Plot3D[Evaluate[PDF[dist2, {x, y}]], {x, -2, 2}, {y, -2, 2}]

enter image description here

test = RandomVariate[dist2, 1000];
Correlation @@ Transpose[test]

yielded 0.79

enter image description here

EstimatedDistribution[test[[All, 1]], CauchyDistribution[a, b]]

yielded: CauchyDistribution[1.01444, 1.01174]

DistributionFitTest[test[[All, 1]], 
 CauchyDistribution[1.0144439384993755`, 1.0117371023486896`]]

yielded: 0.914376

EstimatedDistribution[test[[All, 2]], CauchyDistribution[a, b]]

yielded: CauchyDistribution[1.04505, 1.00878]


DistributionFitTest[test[[All, 2]], 
 CauchyDistribution[1.0450545242904905`, 1.0087772896376905`]]

yielded: 0.229244

If I have misconceived let me know and I will delete.


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