compareEstimation {leptokurticMixture}

Compare the two methods of estimation

Description

Compare the two methods of estimation for fitting a finite mixture of multivariate elliptical leptokurtic-normal distributions; fixed point iterations and MM algorithm.

Usage

compareEstimation(
  mod = NULL,
  data = NULL,
  G = NULL,
  n = 10^4,
  tol = 1e-06,
  wt = NULL,
  n0 = 25,
  lab = NULL
)

Arguments

mod

A character of length 4 such as "VVVV", indicating the model; the covariance and beta parameters.

data

A n x p matrix of observations.

G

The number of components to fit.

n

The maximum number of EM iterations.

tol

The tolerance for the stopping rule; lack of progress. The default is 1e-6 but it depends on the dataset.

wt

a (n x d) matrix of weights for initialization if NULL, then a random weight matrix is generated.

n0

Given wt, the number of iterations used to obtain the initial parameters

lab

Using given labels (lab) as starting values.

Value

A vector of times, number of iterations and log-likelihood values.