m.step {ContaminatedMixt} | R Documentation |
M-step of the EM algorithm for Parsimonious Normal Mixtures
Description
Carries out the M-step for EM algorithm
Usage
m.step(X, modelname, z, mtol=1e-10, mmax=10)
Arguments
X |
a matrix such that |
modelname |
A three letter sequence indicating the covariance structure.
Possible values are: |
z |
A matrix of weights such that |
mtol |
The convergence criteria for the M-step if an iterative procedure is necessary. |
mmax |
The maximum number of iterations for an iterative procedure. |
Value
A list of the model parameters with the mu
, Sigma
, invSigma
and px
for each group.
Author(s)
Antonio Punzo, Angelo Mazza, Paul D. McNicholas
References
Punzo A., Mazza A. and McNicholas P. D. (2018). ContaminatedMixt: An R Package for Fitting Parsimonious Mixtures of Multivariate Contaminated Normal Distributions. Journal of Statistical Software, 85(10), 1–25.
Punzo A. and McNicholas P. D. (2016). Parsimonious mixtures of multivariate contaminated normal distributions. Biometrical Journal, 58(6), 1506–1537.
See Also
Examples
point <- c(0,0,0)
mu <- c(1,-2,3)
Sigma <- diag(3)
alpha <- 0.8
eta <- 5
f <- dCN(point, mu, Sigma, alpha, eta)
x <- rCN(10, mu, Sigma, alpha, eta)