Description Usage Arguments Details Value
Fits a beta mixture model for any number of classes
1  | 
Y | 
 Data matrix (n x j) on which to perform clustering  | 
w | 
 Initial weight matrix (n x k) representing classification  | 
maxiter | 
 Maximum number of EM iterations  | 
tol | 
 Convergence tolerance  | 
weights | 
 Case weights  | 
verbose | 
 Verbose output?  | 
Typically not be called by user.
A list of parameters representing mixture model fit, including posterior weights and log-likelihood
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