'Estimate the precisions parameters of the precision distribution.
Parameters
nk : array-like, shape (n_components,)
xk : array-like, shape (n_components, n_features)
sk : array-like
The shape depends of `covariance_type`:
\'full\' : (n_components, n_features, n_features)
\'tied\' : (n_features, n_features)
\'diag\' : (n_components, n_features)
\'spherical\' : (n_components,)'

def _estimate_precisions(self, nk, xk, sk):

    {'full': self._estimate_wishart_full, 'tied': self._estimate_wishart_tied, 'diag': self._estimate_wishart_diag, 'spherical': self._estimate_wishart_spherical}[self.covariance_type](nk, xk, sk)
    self.precisions_cholesky_ = _compute_precision_cholesky(self.covariances_, self.covariance_type)
