#' Observations (DV), individual predictions (IPRED) and population predictions
#' (IPRED) plotted against the independent variable (IDV), for Xpose 4
#'
#' This is a compound plot consisting of plots of observations (DV), individual
#' predictions (IPRED), and population predictions (PRED) against the
#' independent variable (IDV), a specific function in Xpose 4. It is a wrapper
#' encapsulating arguments to the \code{xpose.plot.default} function.
#'
#' A wide array of extra options controlling \code{xyplots} are available. See
#' \code{\link{xpose.plot.default}} and \code{\link{xpose.panel.default}} for
#' details.
#'
#' @param object An xpose.data object.
#' @param ylb A string giving the label for the y-axis. \code{NULL} if none.
#' @param layout A list controlling the number of columns and rows in a
#' compound plot. The default is 2 columns and 1 row.
#' @param smooth Logical value indicating whether an x-y smooth should be
#' superimposed. The default is TRUE.
#' @param scales A list to be used for the \code{scales} argument in
#' \code{xyplot}.
#' @param \dots Other arguments passed to \code{link{xpose.plot.default}}.
#' @return Returns a compound plot comprising plots of observations (DV),
#' individual predictions (IPRED), and population predictions (PRED) against
#' the independent variable (IDV).
#' @author E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins
#' @seealso \code{\link{dv.vs.idv}}, \code{\link{ipred.vs.idv}},
#' \code{\link{pred.vs.idv}}, \code{\link{xpose.plot.default}},
#' \code{\link{xpose.panel.default}}, \code{\link[lattice]{xyplot}},
#' \code{\link{xpose.prefs-class}}, \code{\link{xpose.data-class}}
#' @keywords methods
#' @examples
#'
#' ## Here we load the example xpose database
#' xpdb <- simpraz.xpdb
#'
#' dv.preds.vs.idv(xpdb)
#'
#' @export dv.preds.vs.idv
#' @family specific functions
"dv.preds.vs.idv" <-
function(object,
#main = NULL,
ylb = "Observations/Predictions",
#xlb = xlabel(xvardef("idv",object),object),
layout=c(3,1),
#subset = xsubset(object),
#onlyfirst = FALSE,
#inclZeroWRES = FALSE,
smooth=TRUE,
scales=list(),
...)
{
## Make sure we have the necessary variables defined in the
## object.
if(is.null(check.vars(c("id","idv","dv","pred","ipred"),object))) {
return(NULL)
}
if(is.null(scales$x$relation)) scales$x$relation="same"
xplot <- xpose.plot.default(xvardef("idv",object),
c(xvardef("dv",object),
xvardef("ipred",object),
xvardef("pred",object)),
object,
scales=scales,
#xlb=xlb,
ylb=ylb,
#main=main,
layout=layout,
#abline=abline,
#lmline=lmline,
#subset=subset,
smooth=smooth,
...)
return(xplot)
}
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