xpose4 (version 4.5.3)

autocorr.wres: Autocorrelation of weighted residuals for Xpose 4

Description

This is an autocorrelation plot of weighted residuals. Most of the options take their default values from the xpose.data object but may be overridden by supplying them as arguments.

Usage

autocorr.wres(object,
           type="p",
           smooth=TRUE,
           ids=F,
           main = "Default",
           ...)
autocorr.iwres(object,
           type="p",
           smooth=TRUE,
           ids=F,
           main = "Default",
           ...)

Arguments

object

An xpose.data object.

smooth

Logical value indicating whether a smooth should be superimposed.

type

1-character string giving the type of plot desired. The following values are possible, for details, see plot: '"p"' for points, '"l"' for lines, '"o"' for overplotted points and lines, '"b"', '"c"') for (empty if '"c"') points joined by lines, '"s"' and '"S"' for stair steps and '"h"' for histogram-like vertical lines. Finally, '"n"' does not produce any points or lines.

ids

A logical value indicating whether text labels should be used as plotting symbols (the variable used for these symbols indicated by the idlab xpose data variable).

main

The title of the plot. If "Default" then a default title is plotted. Otherwise the value should be a string like "my title" or NULL for no plot title. For "Default" the function xpose.multiple.plot.title is used.

…

Other arguments passed to link{xpose.plot.default}.

Value

Returns an aotocorrelation plot for weighted population residuals (WRES) or individual weighted residuals (IWRES).

Details

A wide array of extra options controlling xyplots are available. See xpose.plot.default for details.

See Also

xyplot, xpose.prefs-class, xpose.data-class

Examples

## We expect to find the required NONMEM run and table files for run
## 5 in the current working directory
xpdb5 <- xpose.data(5)


## Here we load the example xpose database 
data(simpraz.xpdb)
xpdb <- simpraz.xpdb

## A vanilla plot
autocorr.wres(xpdb)

## A conditioning plot
autocorr.wres(xpdb, dilution=TRUE)

## Custom heading and axis labels
autocorr.wres(xpdb, main="My conditioning plot", ylb="|CWRES|", xlb="PRED")

## Custom colours and symbols, IDs
autocorr.wres(xpdb, cex=0.6, pch=3, col=1, ids=TRUE)

## A vanilla plot with IWRES
autocorr.iwres(xpdb)