Nothing
#' @export
#'
print.externX = function(x, ...){
if(!inherits(x, "externX")) stop("use only with\"externX\" objects")
cat("Secondary multinomial model for external class predictor", "\n")
cat(" fitted by maximum likelihood method", "\n")
if(x$varest == "none") cat(" primary model variance not accounted for", "\n")
if(x$varest == "Hessian") cat(" primary model variance accounted for through the hessian of the joint likelihood", "\n")
if(x$varest == "paramBoot") cat(" primary model variance accounted for through parametric boostrap", "\n")
cl <- x$call
cl$B <- NULL
if(is.data.frame(cl$data))
{
cl$data <- NULL
x$call$data <- NULL
}
cat(" \n")
dput(cl)
cat(" \n")
posfix <- eval(cl$posfix)
cat("Statistical Model:", "\n")
cat(paste(" Dataset:", x$call$data),"\n")
cat(paste(" Number of subjects:", x$ns),"\n")
cat(paste(" Number of latent classes:", x$ng), "\n")
cat(paste(" Number of parameters:", length(x$best))," \n")
cat(" \n")
cat("Iteration process:", "\n")
if(x$conv==1) cat(" Convergence criteria satisfied")
if(x$conv==2) cat(" Maximum number of iteration reached without convergence")
if(x$conv==3) cat(" Convergence with restrained Hessian matrix")
if(x$conv==4|x$conv==12)
{
cat(" The program stopped abnormally. No results can be displayed.\n")
}
else
{
cat(" \n")
if(x$varest == "paramBoot") {
cat(" Proportion of convergence on bootstrap iterations (%)=", x$Mconv, "\n")
} else {
cat(" Number of iterations: ", x$niter, "\n")
cat(" Convergence criteria: parameters=", signif(x$gconv[1],2), "\n")
cat(" : likelihood=", signif(x$gconv[2],2), "\n")
cat(" : second derivatives=", signif(x$gconv[3],2), "\n")
}
cat(" \n")
cat("Goodness-of-fit statistics:", "\n")
cat(paste(" maximum log-likelihood:", round(x$loglik,2))," \n")
cat(paste(" AIC:", round(x$AIC,2))," \n")
cat(paste(" BIC:", round(x$BIC,2))," \n")
cat(" \n")
}
}
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