Nothing
mlest<-function(data,...)
{
# Takes MVN data with missing values and calculates the MLE of the mean vector and the var-cov matrix
data<-as.matrix(data)
sortlist<-mysort(data) # put data with identical patterns of missingness together
nvars<-ncol(data)
nobs<-nrow(data)
if(nvars>50)
stop("mlest cannot handle more than 50 variables.")
startvals<-getstartvals(data) # find starting values
lf<-getclf(data=sortlist$sorted.data, freq=sortlist$freq)
mle<-nlm(lf,startvals,...)
muhat<-mle$estimate[1:nvars] # extract estimates of mean
del<-make.del(mle$estimate[-(1:nvars)]) # extract estimates of sigmahat
factor<-solve(del,diag(nvars))
sigmahat<-t(factor) %*% factor
list(muhat=muhat, sigmahat=sigmahat, value=mle$minimum, gradient=mle$gradient,
stop.code=mle$code, iterations=mle$iterations)
}
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