For computing log-likelihood of points being in a certain multivariate distribution I am trying to invert the covariance matrix $\Sigma$. Unfortunately, $\Sigma$ turned out to be singular, with multiple zero eigenvalues. Using pseudo-inverse leads to very low log-likelihood, which is expected. How could I address this? Would it help to reduce the dimension of the problem?