cwm (version 0.0.3)

stepCwr: Function to estimate CWR models via multiple EM algorithm restarts

Description

This function iteratens nIter times a single estimation of CWR models by cwrEm function. Then the one that has best logLikelihood is chosen.

Usage

stepCwr(X, Y, nc, prop = 0.1, nIter = 10, changeTrainingSet = FALSE)

Arguments

X

X data vector

Y

Y data vector

nc

number of clusters.

prop

Proportion of samples. Default 0.1.

nIter

Number of iteration. Default 10.

changeTrainingSet

Boolean. If TRUE the training set is changed.

Value

A cwr object.

Details

This function allows the estimation of models where the structure of the data set lies to probable convergence problems.

References

Murphy, Bettina.

See Also

cwrEm

Examples

data(geyser)
x=geyser[,1]
y=geyser[,2]                            
ciao=stepCwr(x,y,nc=2)