absval.wres.vs.cov.bw {xpose4}

Absolute weighted residuals vs covariates for Xpose 4

Description

This creates a stack of box and whisker plot of absolute population weighted residuals (|WRES| or |iWRES|) vs covariates. It is a wrapper encapsulating arguments to the xpose.plot.bw function. Most of the options take their default values from the xpose.data object but may be overridden by supplying them as arguments.

Usage

absval.wres.vs.cov.bw(object, xlb = "|WRES|", main = "Default", ...)

Arguments

object

An xpose.data object.

xlb

A string giving the label for the x-axis. NULL if none.

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.

...

Other arguments passed to xpose.plot.bw.

Details

Each of the covariates in the Xpose data object, as specified in object@Prefs@Xvardef$Covariates, is evaluated in turn, creating a stack of plots.

A wide array of extra options controlling box-and-whisker plots are available. See xpose.plot.bw for details.

Value

Returns a stack of box-and-whisker plots of |WRES| vs covariates.

Author(s)

E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins

See Also

xpose.plot.bw, xpose.panel.bw, bwplot, xpose.prefs-class, xpose.data-class

Other specific functions: absval.cwres.vs.cov.bw(), absval.cwres.vs.pred(), absval.cwres.vs.pred.by.cov(), absval.iwres.cwres.vs.ipred.pred(), absval.iwres.vs.cov.bw(), absval.iwres.vs.idv(), absval.iwres.vs.ipred(), absval.iwres.vs.ipred.by.cov(), absval.iwres.vs.pred(), absval.wres.vs.idv(), absval.wres.vs.pred(), absval.wres.vs.pred.by.cov(), absval_delta_vs_cov_model_comp, addit.gof(), autocorr.cwres(), autocorr.iwres(), autocorr.wres(), basic.gof(), basic.model.comp(), cat.dv.vs.idv.sb(), cat.pc(), cov.splom(), cwres.dist.hist(), cwres.dist.qq(), cwres.vs.cov(), cwres.vs.idv(), cwres.vs.idv.bw(), cwres.vs.pred(), cwres.vs.pred.bw(), cwres.wres.vs.idv(), cwres.wres.vs.pred(), dOFV.vs.cov(), dOFV.vs.id(), dOFV1.vs.dOFV2(), data.checkout(), dv.preds.vs.idv(), dv.vs.idv(), dv.vs.ipred(), dv.vs.ipred.by.cov(), dv.vs.ipred.by.idv(), dv.vs.pred(), dv.vs.pred.by.cov(), dv.vs.pred.by.idv(), dv.vs.pred.ipred(), gof(), ind.plots(), ind.plots.cwres.hist(), ind.plots.cwres.qq(), ipred.vs.idv(), iwres.dist.hist(), iwres.dist.qq(), iwres.vs.idv(), kaplan.plot(), par_cov_hist, par_cov_qq, parm.vs.cov(), parm.vs.parm(), pred.vs.idv(), ranpar.vs.cov(), runsum(), wres.dist.hist(), wres.dist.qq(), wres.vs.idv(), wres.vs.idv.bw(), wres.vs.pred(), wres.vs.pred.bw(), xpose.VPC(), xpose.VPC.both(), xpose.VPC.categorical(), xpose4-package

Examples

## Not run: 
## 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
absval.wres.vs.cov.bw(xpdb)

## A custom plot
absval.wres.vs.cov.bw(xpdb, bwdotcol="white", 
  bwdotpch=15,
  bwreccol="red",
  bwrecfill="red",
  bwumbcol="red",
  bwoutpch=5,
  bwoutcol="black")

## A vanilla plot using IWRES
absval.iwres.vs.cov.bw(xpdb)

## End(Not run)