Attempt Model Fit and Return Quality Metrics.
ChooseK.iter(data, k, init_means, fix_means, init_covs, init_props, maxit, eps)
Numeric data matrix.
Number of clusters.
Optional list of initial mean vectors.
Fix the means to their starting value? Must initialize.
Optional list of initial covariance matrices.
Optional vector of initial cluster proportions.
Maximum number of EM iterations.
Minimum acceptable increment in the EM objective.
Numberic vector containing the 4 cluster quality metrics. Returns null if the model fails to fit.