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I want to calculate the Kullback Leibler divergence between a multivariate t distribution and a multivariate normal distribution, for different values of the degrees of freedom $\nu$.

However, this requires a multiple integration that seems to be difficult to calculate numerically for dimensions larger than 2. Is there a known result to calculate this integral or a numerical trick?

I understand there are general multivariate numerical integration methods. I was just wondering if there is a simpler ad hoc tool I could use as these are popular distributions, so I guess there may be some simpler tools.

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  • $\begingroup$ Monte Carlo integration? $\endgroup$ – seanv507 Feb 7 at 12:17
  • $\begingroup$ @seanv507 Thanks, that is too general to be of any use, but I appreciate the pointer. $\endgroup$ – Pullback Feb 7 at 13:20
  • $\begingroup$ t-distribution is a scale mixture of Gaussian distributions and fining KL divergence to mixtures is notoriously difficult. You can lower bound on it if you are interested. $\endgroup$ – passerby51 Feb 7 at 15:13
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There is a numerical solution based on one-dimensional numerical integrals here:

Kullback Leibler divergence between a multivariate t and a multivariate normal distributions

enter image description here

I doubt there is a closed form solution, but the 1D numerical integral seems simple.

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