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.
Rini (2021). Gaussian mixture model parameter estimation with prior hyper parameters (https://www.mathworks.com/matlabcentral/fileexchange/52775-gaussian-mixture-model-parameter-estimation-with-prior-hyper-parameters), MATLAB Central File Exchange. Retrieved .
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