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#' Retrieve a briefing for complete, conditional and general dominance
#'
#' @param da.object a \code{dominanceAnalysis} object
#' @param fit.functions name of the fit indices to retrieve. If NULL, all fit indices will be retrieved
#' @param abbrev if TRUE
#' @return a list. Each element is a data.frame, that comprises the dominance analysis
#' for a specific fit index. Each data.frame have the predictors as row
#' and each column reports the predictors that are dominated for each predictor
#' @export
#' @family retrieval methods
#' @examples
#' # For matrix or data.frame
#' data(longley)
#' da.longley<-dominanceAnalysis(lm(Employed~.,longley))
#' dominanceBriefing(da.longley, abbrev=FALSE)
#' dominanceBriefing(da.longley, abbrev=TRUE)
dominanceBriefing<-function(da.object, fit.functions=NULL, abbrev=FALSE) {
checkDominanceAnalysis(da.object)
if(is.null(fit.functions)) {
fit.functions=da.object$fit.functions
}
abbrev.matrix<-function(m) {
n=rownames(m)
n=abbreviate(n)
rownames(m)<-n
colnames(m)<-n
m
}
if(abbrev) {
process.names<-abbrev.matrix
} else {
process.names<-I
}
names(fit.functions)<-fit.functions
rank.f<-function(type,fit) {
rankUsingMatrix(process.names(dominanceMatrix(da.object, type=type, fit.functions=fit)))
}
out<-lapply(fit.functions, function(fit) {
rank.complete = rank.f('complete', fit)
rank.conditional = rank.f('conditional', fit)
rank.general = rank.f('general', fit)
out<-data.frame(complete=rank.complete,conditional=rank.conditional, general=rank.general)
rownames(out)<-replaceTermsInString(da.object$predictors,da.object$terms)
out
})
class(out)<-c("dominanceBriefing","list")
out
}
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