I am currently playing around with Gaussian Mixture Models in order to model stock returns. Part of all this is using the EM algorithm to obtain MLE of parameters. I have found a package in R (mixtools) that provides the functions normalmixEM and mvnormalmixEM. I have tried it but I don't understand the output for mvnormalmix (my input consisted of a 200x2 matrix): Why do I get for two components two 2x1 mu-vectors and why do I get two 2x2 covariance matrices? Isn't that one too many?
If you could clear that up or give me a link where the output of the multivariate case is explained (because I find it in general a bit confusing) I would very much appreciate it.