xpose4 (version 4.7.3)

dv.vs.pred: Observations (DV) plotted against population predictions (PRED) for Xpose 4

Description

This is a plot of observations (DV) vs population predictions (PRED), a specific function in Xpose 4. It is a wrapper encapsulating arguments to the xpose.plot.default function. Most of the options take their default values from xpose.data object but may be overridden by supplying them as arguments.

Usage

dv.vs.pred(object, abline = c(0, 1), smooth = TRUE, ...)

Value

Returns an xyplot of DV vs PRED.

Arguments

object

An xpose.data object.

abline

Vector of arguments to the panel.abline function. No abline is drawn if NULL.

smooth

Logical value indicating whether an x-y smooth should be superimposed. The default is TRUE.

...

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

Author

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

Details

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

See Also

xpose.plot.default, xpose.panel.default, xyplot, 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.cov.bw(), 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.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

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

## A vanilla plot
dv.vs.pred(xpdb)

## A conditioning plot
dv.vs.pred(xpdb, by="HCTZ")