#' Absolute population weighted residuals vs population predictions, and
#' absolute individual weighted residuals vs individual predictions, for Xpose
#' 4
#'
#' This is a matrix plot of absolute population weighted residuals (|CWRES|) vs
#' population predictions (PRED) and absolute individual weighted residuals
#' (|IWRES|) vs individual predictions (IPRED), a specific function in Xpose 4.
#' It is a wrapper encapsulating arguments to the \code{absval.cwres.vs.pred}
#' and \code{absval.iwres.vs.ipred} functions.
#'
#' The plots created by the \code{absval.wres.vs.pred} and
#' \code{absval.iwres.vs.ipred} functions are presented side by side for
#' comparison.
#'
#' A wide array of extra options controlling xyplots are available. See
#' \code{\link{xpose.plot.default}} for details.
#'
#' @aliases absval.iwres.wres.vs.ipred.pred absval.iwres.cwres.vs.ipred.pred
#' @param object An xpose.data object.
#' @param main The title of the plot. If \code{"Default"} then a default title
#' is plotted. Otherwise the value should be a string like \code{"my title"} or
#' \code{NULL} for no plot title.
#' @param \dots Other arguments passed to \code{link{xpose.plot.default}}.
#' @return Returns a compound plot.
#' @author E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins
#' @seealso \code{\link{absval.wres.vs.pred}},
#' \code{\link{absval.iwres.vs.ipred}}, \code{\link{xpose.plot.default}},
#' \code{\link{xpose.panel.default}}, \code{\link[lattice]{xyplot}},
#' \code{\link{xpose.prefs-class}}, \code{\link{xpose.data-class}}
#' @examples
#'
#' ## Here we load the example xpose database
#' xpdb <- simpraz.xpdb
#'
#' ## A vanilla plot
#' absval.iwres.wres.vs.ipred.pred(xpdb)
#' absval.iwres.cwres.vs.ipred.pred(xpdb)
#'
#' ## Custom colours and symbols
#' absval.iwres.cwres.vs.ipred.pred(xpdb, cex=0.6, pch=8, col=1)
#'
#' @export
#' @family specific functions
absval.iwres.cwres.vs.ipred.pred <-
function(object,
##aspect="fill",
main="Default",
...) {
if(is.null(check.vars(c("pred","cwres","iwres","ipred"),
object,silent=FALSE))) {
return()
}
num.of.plots <- 2
plotList <- vector("list",num.of.plots)
plot1 <- absval.cwres.vs.pred(object,main=NULL,
##aspect=aspect,
pass.plot.list=TRUE,
...)
plot2 <- absval.iwres.vs.ipred(object,main=NULL,
##aspect=aspect,
pass.plot.list=TRUE,
...)
plotList[[1]] <- plot1
plotList[[2]] <- plot2
default.plot.title <- "(Conditional) Weighted residuals vs. Predictions"
plotTitle <- xpose.multiple.plot.title(object=object,
plot.text = default.plot.title,
main=main,
...)
obj <- xpose.multiple.plot(plotList,plotTitle,...)
return(obj)
}
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