Nothing
########################################################################################################################
## Surcharge de la fonction print
########################################################################################################################
#'
#' Print function.
#'
#' This function gives the print of an instance of \code{\linkS4class{VSLCMresults}}.
#'
#' @param x instance of \code{\linkS4class{VSLCMresults}}.
#'
#' @name print
#' @rdname print-methods
#' @docType methods
#' @exportMethod print
#' @aliases print print,VSLCMresults-method
setMethod(
f="print",
signature = c("VSLCMresults"),
definition = function(x){
cat("Data set:\n Number of individuals:", x@data@n,"\n")
if (x@data@withContinuous){
cat(" Number of continuous variables:", x@data@dataContinuous@d, "\n")
val <- round(100*(1-mean(x@data@dataContinuous@notNA)),2)
if (val>0)
cat(" Percentile of missing values for the continuous variables:", val,"\n")
}
if (x@data@withInteger){
cat(" Number of count variables:", x@data@dataInteger@d, "\n")
val <- round(100*mean(1-x@data@dataInteger@notNA),2)
if (val>0)
cat(" Percentile of missing values for the integer variables:", val,"\n")
}
if (x@data@withCategorical){
cat(" Number of categorical variables:", x@data@dataCategorical@d, "\n")
miss <- 100*sum(sweep(is.na(x@data@dataCategorical@data),1,x@data@dataCategorical@weightdata,"*")) / (x@data@n * x@data@dataCategorical@d)
if (miss>0)
cat(" Percentile of missing values for the categorical variables:", miss,"\n")
}
cat("\n")
cat("Model:\n Number of components:", x@model@g, "\n")
cat(" Model selection has been performed according to the", x@strategy@crit.varsel, " criterion \n")
if (x@strategy@vbleSelec) cat(" Variable selection has been performed,", sum(x@model@omega)," (", round(100*sum(x@model@omega)/length(x@model@omega), 2),"% ) of the variables are relevant for clustering \n \n")
if ((length(x@criteria@degeneracyrate)==1)&&(x@criteria@degeneracyrate != 1)){
cat("Information Criteria:\n")
cat(" loglike:", x@criteria@loglikelihood,"\n")
cat(" AIC: ", x@criteria@AIC,"\n")
cat(" BIC: ", x@criteria@BIC,"\n")
cat(" ICL: ", x@criteria@ICL,"\n")
if ((x@strategy@crit.varsel=="MICL")&&(x@strategy@vbleSelec==TRUE)){
cat(" MICL: ", x@criteria@MICL,"\n")
cat(" Best values has been found ", x@criteria@cvrate, "times\n")
}
}
cat("\n")
if ((length(x@criteria@degeneracyrate)==1) && (x@criteria@degeneracyrate>0.1))
cat("Warnings:\n The rate of degeneracy for the EM algorithm is", x@criteria@degeneracyrate,"\n" )
}
)
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