I am trying to analytically compute the posterior distribution for a simple dataset. I have a multi-variate Gaussian likelihood and a discrete uniform prior. I am multiplying my prior with my likelihood to get a Gaussian mixture with n terms. I am not sure how to then analytically compute the pdf from this, I don't have any experience with mixture models. Any help would be appreciated!