Multivariate mixture models provide a convenient method of densityestimation and model based clustering as well as providing possible explanations for the actual data generationprocess. But the problem of choosing the number of components ($g$) in a statistically meaningful way is still asubject...

An almost nonparametric approach for the estimation of the mixing proportion in a mixture of two distributions, when we have a vector of observations on each subject, is to define a mixture of binomials. A mixture of binomials can be obtained if the vector of observations is mapped into a vector...

Parameter identifiability is very useful if one wishes to make inferences in a statistical model. There are two important nonidentifiabilities in finite mixture models : boundary nonidentifiability and label nonidentifiability. Although parameters are not identifiable in the strict sense, in...