The bivariate von Mises distribution is a probability distribution defined on the torus,
in
.
The probability density function of the general bivariate von Mises distribution for the angles
is given by[1]
![{\displaystyle f(\phi ,\psi )\propto \exp[\kappa _{1}\cos(\phi -\mu )+\kappa _{2}\cos(\psi -\nu )+(\cos(\phi -\mu ),\sin(\phi -\mu ))\mathbf {A} (\cos(\psi -\nu ),\sin(\psi -\nu ))^{T}],}](https://wikimedia.org/api/rest_v1/media/math/render/svg/3d9a7ecf23b97122c3a20c3fee459a81f9a7f155)
where
and
are the means for
and
,
and
their concentration and the matrix
is related to their correlation.
Two commonly used variants of the bivariate von Mises distribution are the sine and cosine variant.
The cosine variant of the bivariate von Mises distribution[3] has the probability density function
![{\displaystyle f(\phi ,\psi )=Z_{c}(\kappa _{1},\kappa _{2},\kappa _{3})\ \exp[\kappa _{1}\cos(\phi -\mu )+\kappa _{2}\cos(\psi -\nu )-\kappa _{3}\cos(\phi -\mu -\psi +\nu )],}](https://wikimedia.org/api/rest_v1/media/math/render/svg/25897440a701bf50b7b0e4c7191678692d0344a2)
where
and
are the means for
and
,
and
their concentration and
is related to their correlation.
is the normalization constant. This distribution with
=0 has been used for kernel density estimates of the distribution of the protein dihedral angles
and
.[4]
The sine variant has the probability density function[5]
![{\displaystyle f(\phi ,\psi )=Z_{s}(\kappa _{1},\kappa _{2},\kappa _{3})\ \exp[\kappa _{1}\cos(\phi -\mu )+\kappa _{2}\cos(\psi -\nu )+\kappa _{3}\sin(\phi -\mu )\sin(\psi -\nu )],}](https://wikimedia.org/api/rest_v1/media/math/render/svg/8d9eb5705daadc9c49c0872f0f3edeee8600f17e)
where the parameters have the same interpretation.