Gaussian mixture model parameter estimation with prior hyper parameters

There are quite a few Expectation Maximization based Gaussian mixture models. However, the models do not set any prior for mean and variance. I have implemented a 1D GMM inspired by Chris McCormick. Such a model can be helpful in cases where the data range is small and will prevent kernel overlap by restricting the kernels around the prior values.