xpose4 (version 4.7.1)

wres.vs.pred: Population weighted residuals (WRES) plotted against population predictions (PRED) for Xpose 4

Description

This is a plot of population weighted residuals (WRES) 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

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

Arguments

object

An xpose.data object.

smooth

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

abline

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

…

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

Value

Returns an xyplot of WRES vs PRED.

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

Other specific functions: absval.cwres.vs.cov.bw(), absval.cwres.vs.pred.by.cov(), absval.cwres.vs.pred(), absval.iwres.cwres.vs.ipred.pred(), absval.iwres.vs.cov.bw(), absval.iwres.vs.idv(), absval.iwres.vs.ipred.by.cov(), absval.iwres.vs.ipred(), absval.iwres.vs.pred(), absval.wres.vs.cov.bw(), absval.wres.vs.idv(), absval.wres.vs.pred.by.cov(), absval.wres.vs.pred(), 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.bw(), cwres.vs.idv(), cwres.vs.pred.bw(), cwres.vs.pred(), 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.by.cov(), dv.vs.ipred.by.idv(), dv.vs.ipred(), dv.vs.pred.by.cov(), dv.vs.pred.by.idv(), dv.vs.pred.ipred(), dv.vs.pred(), gof(), ind.plots.cwres.hist(), ind.plots.cwres.qq(), ind.plots(), 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.bw(), wres.vs.idv(), wres.vs.pred.bw(), xpose.VPC.both(), xpose.VPC.categorical(), xpose.VPC(), xpose4-package

Examples

# NOT RUN {
## Here we load the example xpose database 
xpdb <- simpraz.xpdb

wres.vs.pred(xpdb)

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

# }