Compare the two methods of estimation for fitting a finite mixture of multivariate elliptical leptokurtic-normal distributions; fixed point iterations and MM algorithm.
compareEstimation(
mod = NULL,
data = NULL,
G = NULL,
n = 10^4,
tol = 1e-06,
wt = NULL,
n0 = 25,
lab = NULL
)A vector of times, number of iterations and log-likelihood values.
A character of length 4 such as "VVVV", indicating the model; the covariance and beta parameters.
A n x p matrix of observations.
The number of components to fit.
The maximum number of EM iterations.
The tolerance for the stopping rule; lack of progress. The default is 1e-6 but it depends on the dataset.
a (n x d) matrix of weights for initialization if NULL, then a random weight matrix is generated.
Given wt, the number of iterations used to obtain the initial parameters
Using given labels (lab) as starting values.