Given a matrix of random vectors, estimates the parameters for a mixture of multivariate normal distributions. Accommodates arbitrary patterns of missingness, provided the elements are missing at random (MAR).
fit.mix(
data,
k = 2,
init_means = NULL,
fix_means = FALSE,
init_covs = NULL,
init_props = NULL,
maxit = 100,
eps = 1e-06,
report = FALSE
)
Numeric data matrix.
Number of mixture components. Defaults to 2.
Optional list of initial mean vectors.
Fix means to their starting values? 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.
Report fitting progress?
Object of class mix
containing the estimated