Nothing
est.mcfa <- function(init_para, Y, itmax, tol, conv_measure, ...) {
p <- ncol(Y)
n <- nrow(Y)
init_para$logL <- do.call("loglike.mcfa", c(list(Y=Y), init_para))
if (any(class(init_para$logL) %in% "try-error") ||
any(class(init_para$logL) %in% 'character')) {
FIT <- paste('in computing the log-likelihood before EM-steps')
class(FIT) <- "error"
return(FIT)
}
for (niter in 1 : itmax) {
FIT <- do.call('Mstep.mcfa', c(list(Y = Y), init_para))
if (any(class(FIT) %in% 'error')) {
FIT <- paste('in ', niter,
'iteration of the M-step:',
FIT)
class(FIT) <- "error"
return(FIT)
}
FIT$logL <- try(do.call('loglike.mcfa', c(list(Y = Y), FIT)))
if (any(class(FIT$logL) %in% "try-error") ||
any(class(FIT$logL) %in% 'character')) {
FIT <- paste('in computing the log-likelihood after the ', niter,
'th the M-step', FIT$logL, sep = '')
class(FIT) <- "error"
return(FIT)
}
if ((FIT$logL == -Inf) | is.na(FIT$logL)){
FIT <- paste('Log likelihood computed after the', niter,
'th iteration of the M-step is not finite', sep='')
class(FIT) <- "error"
return(FIT)
}
if ((conv_measure == "diff") && (abs(FIT$logL - init_para$logL) < tol))
break
if ((conv_measure == "ratio") &&
(abs((FIT$logL - init_para$logL)/FIT$logL) < tol))
break
init_para <- FIT
}
class(FIT) <- "mcfa"
return(FIT)
}
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