| dv.vs.pred {xpose4} | R Documentation |
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, ...)
Arguments
object |
An xpose.data object. |
abline |
Vector of arguments to the |
smooth |
Logical value indicating whether an x-y smooth should be superimposed. The default is TRUE. |
... |
Other arguments passed to |
Details
A wide array of extra options controlling xyplots are available. See
xpose.plot.default and xpose.panel.default for
details.
Value
Returns an xyplot of DV vs PRED.
Author(s)
E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins
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")