SDMIXTURE Estimating Gaussian mixture model P=SDMIXTURE(DATA,options) INPUT DATA data set object OUTPUT P mixture model pipeline OPTIONS 'comp' number of components per class (def: 'auto' = choose automatically) 'maxsamples' maximum number of samples used for initialization (def: 500) 'iter' number of iterations (def: 30). If iter==[], use the likelihood delta to stop 'delta' likelihood change to use as stopping crit (def: 1e-4) 'cluster' return clustering result (one output per component) 'prior' class priors (default: use priors from the training set) DESCRIPTION SDMIXTURE estimate Gaussian mixture model for each class in DATA. By default, the number of mixture components is estimated from data based on non-parameteric density estimator. Number of components may be also provided in the 'comp' option. SDMIXTURE may be used for unsupervised cluster analysis using the 'cluster' option. If specified, SDMIXTURE will perform mixture estimation on each class present and return one output per cluster. READ MORE http://doc.prsdstudio.com/latest/guide/classifiers.html#sdmixture
sdmixture is referenced in examples: