estim.mmeln: Maximum Likelihood estimation of the model parameters

In giguerch/mmeln: Estimation of Multinormal Mixture Distribution

Maximum Likelihood estimation of the model parameters

Description

Compute the MLE of the model parameters using the E-M (Expectation-Maximization) algorithm

Usage

## S3 method for class 'mmeln'
estim(X,...,mu=NULL,tau=NULL,sigma=NULL,random.start=FALSE,iterlim=500,tol=1e-8)

Arguments

X	An object of type mmeln containing the design of the model, see mmeln
...	For the moments no other arguments can be added
mu	A list of length X$G containing the starting value for the location parameters
tau	The starting value for the mixture parameters
sigma	A list of length X$G containing the starting value for the covariances parameters
random.start	A True/False value indicating if the starting parameters should be given at random. If true the starting values are not needed.
iterlim	The maximum number of iterations allowed
tol	Tolerance, degree of precision required to stop the iterative process

Details

Methods estim.mmeln... are used by the estim function but are of no use outside this method.

Value

Retourne un objet de type "mmeln" & "mmelnSOL" les arguments suivants :

obj$Y	The data matrix
obj$G	The number of groups
obj$p	Number of column in Y
obj$N	Number of row in Y
obj$Xg	The list of location design matrices
obj$pl	The number of location parameters
obj$Z	Mixture design matrix
obj$pm	The number of mixture parameters
obj$cov	Covariance type
obj$equalcov	logical value indicating if covariance is equal across group
obj$pc	The number of covariance parameters

Author(s)

Charles-Édouard Giguère

References

McLachlan, G. & Peel, D. (2000), Finite mixture models,Wiley

Flury, B. D. (1997), A first course in multivariate statistics, Springer

Pinheiro J. C. and Bates D. M. (2000), Mixed-Effects Models in S and S-PLUS, Springer

Srivastava, M.S. (2002), Methods of Multivariate Statistics, WILEY

Lindstrom M. J. and Bates D. M. (1988), Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-MeasuresData, Journal of the American Statistical Association,American Statistical Association,V. 83,I. 404, P. 1014-1022

See Also

mmeln.package

Examples

data(exY)
### estimation of the parameters of the mixture
temps=0:2
mmeln1=mmeln(Y, G = 3, form.loc = list(~temps, ~temps + I(temps^2),
                       ~temps + I(temps^2)), form.mel = ~SEXE, cov = "CS")
mmelnSOL1=estim(mmeln1,mu = list(c(1,1), c(2,0,0), c(3,0,0)),
    tau = c(0,0,0,0), sigma = list(c(1,0), c(1,0), c(1,0)))

giguerch/mmeln documentation built on Feb. 3, 2024, 5:44 a.m.