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#' @title Selected model of a \code{fusion} object
#' @description The function displays for categorical covariates the selected model of an
#' object of class \code{fusion} as list.
#'
#' @param x an object of class \code{fusion}
#'
#' @details The selected model for each categorical predictor is displayed as a list of length equal
#' to the number of categories after fusion. Fused categories are shown with their original labelling
#' in one list element.
#' The function is only available if effect fusion (method in \code{effectFusion} is unequal to \code{NULL})
#' and final model selection (argument \code{modelSelection} in \code{effectFusion} is not NULL) is performed.
#'
#' See \code{summary.fusion} for more details.
#'
#' @author Daniela Pauger, Magdalena Leitner <effectfusion.jku@gmail.com>
#' @seealso \code{\link{effectFusion}}
#' @export
#'
#' @examples
#' ## see example for effectFusion
#'
model <- function(x) {
stopifnot(is(x, "fusion"))
if (is.null(x$modelSelection)) {
cat("No model selection performed")
} else {
varCat <- x$model$n_ord + x$model$n_nom
sel_mod <- x$refit$model
ind <- c(0, cumsum(c(rep(1, x$model$n_cont), x$model$diff))) + 1
cat <- x$model$categories
for (i in 1:varCat) {
k <- i + x$model$n_cont
if (x$data$types[k] == "o")
S <- getSOrdinal(sel_mod[ind[k]:(ind[k + 1] - 1)])
if (x$data$types[k] == "n")
S <- getSNominal(cat[i], sel_mod[ind[k]:(ind[k + 1] - 1)])
show_model <- list()
if (sum(rowSums(S) == 0) > 0) {
show_model[[1]] <- c(0, which(rowSums(S) == 0))
} else show_model[[1]] <- 0
if (length(show_model[[1]]) != cat[i]) {
if (sum(S[, 1]) == 0) {
for (j in 2:ncol(S)) {
show_model[[j]] <- which(S[, j] == 1)
}
} else {
for (j in 1:ncol(S)) {
show_model[[j + 1]] <- which(S[, j] == 1)
}
}
}
show_model <- lapply(show_model, function(x) {x + 1})
show_model <- lapply(show_model, function(z, x, i) {x$data$levelnames[[i]][z]},
x = x, i = i)
cat("Covariate '", names(x$data$levelnames)[i], "'", sep = "", "\n")
print(show_model)
}
}
}
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