This is a compound plot consisting of plots of observations (DV) vs
population predictions (PRED), observations (DV) vs individual predictions
(IPRED), absolute individual weighted residuals (|IWRES|) vs IPRED, and
weighted population residuals (CWRES) vs independent variable (IDV), a
specific function in Xpose 4. WRES are also supported. It is a wrapper
encapsulating arguments to the dv.vs.pred, dv.vs.ipred,
absval.iwres.vs.ipred and wres.vs.idv functions.
Arguments
- object
An xpose.data object.
- force.wres
Should the plots use WRES? Values can be
TRUE/FALSE. Otherwise the CWRES are used if present.- main
The title of the plot. If
"Default"then a default title is plotted. Otherwise the value should be a string like"my title"orNULLfor no plot title.- use.log
Should we use log transformations in the plots?
- ...
Other arguments passed to
xpose.plot.default.
Value
Returns a compound plot comprising plots of observations (DV) vs population predictions (PRED), DV vs individual predictions (IPRED), absolute individual weighted residuals (|IWRES|) vs IPRED, and weighted populations residuals (WRES) vs the independent variable (IDV).
Details
Four basic goodness-of-fit plots are presented side by side for comparison.
Conditional weighted residuals (CWRES) require some extra steps to
calculate. See compute.cwres for details.
A wide array of extra options controlling xyplots are available. See
xpose.plot.default for details.
basic.gof.cwres is just a wrapper for basic.gof with
use.cwres=TRUE.
See also
dv.vs.pred, dv.vs.ipred,
absval.iwres.vs.ipred, wres.vs.idv,
cwres.vs.idv, xpose.plot.default,
xpose.panel.default, xyplot,
compute.cwres, 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.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
