R/methods.seqimp.R

In seqimpute: Imputation of Missing Data in Sequence Analysis

#' Print a \code{seqimp} object
#' @param x Object of class \code{seqimp}
#' @param ... additional arguments passed to other functions
#'
#' @author Kevin Emery
#' @export
print.seqimp <- function(x, ...) {
  cat("Class: seqimp\n")
  cat("Number of multiple imputations: ", x$m, "\n")
  cat("Method: ", x$method, "\n")
}

#' Summary of a \code{seqimp} object
#' @param object Object of class \code{seqimp}
#' @param ... additional arguments passed to other functions
#'
#' @author Kevin Emery
#' @export
summary.seqimp <- function(object, ...) {
  print(object, ...)
  invisible(object)
}


#' Plot a \code{seqimp} object
#' @description
#' Plot a \code{seqimp} object. The state distribution plot of the first
#' \code{m} completed datasets is shown, possibly alongside the original
#' dataset with missing data
#'
#' @param x Object of class \code{seqimp}
#' @param m Number of completed datasets to show
#' @param include logical that indicates if the original dataset with missing
#' value should be plotted or not
#' @param ... Arguments to be passed to the seqdplot function
#'
#' @author Kevin Emery
#' @export
plot.seqimp <- function(x, m = 5, include = TRUE, ...) {
  tmp <- fromseqimp(x, format = "long", include = include)
  tmp <- tmp[tmp$.imp <= m, -c(2)]
  if ("cluster" %in% colnames(tmp)) {
    tmp <- tmp[, !colnames(tmp) %in% c("cluster")]
  }
  seqtmp <- suppressMessages(TraMineR::seqdef(tmp[, -c(1)]))
  suppressMessages(TraMineR::seqdplot(seqtmp, group = tmp$.imp, ...))
}