dv.vs.pred | R Documentation |
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.
dv.vs.pred(object, abline = c(0, 1), smooth = TRUE, ...)
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 |
A wide array of extra options controlling xyplot
s are available. See
xpose.plot.default
and xpose.panel.default
for
details.
Returns an xyplot of DV vs PRED.
E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins
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
## 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")
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