Absolute weighted residuals vs covariates for Xpose 4
Source:R/absval.wres.vs.cov.bw.R
absval.wres.vs.cov.bw.Rd
This creates a stack of box and whisker plot of absolute population weighted
residuals (|WRES| or |iWRES|) vs covariates. It is a wrapper encapsulating
arguments to the xpose.plot.bw
function. Most of the options take
their default values from the xpose.data object but may be overridden by
supplying them as arguments.
Arguments
- object
An xpose.data object.
- xlb
A string giving the label for the x-axis.
NULL
if none.- main
The title of the plot. If
"Default"
then a default title is plotted. Otherwise the value should be a string like"my title"
orNULL
for no plot title.- ...
Other arguments passed to
xpose.plot.bw
.
Details
Each of the covariates in the Xpose data object, as specified in
object@Prefs@Xvardef$Covariates
, is evaluated in turn, creating a
stack of plots.
A wide array of extra options controlling box-and-whisker plots are
available. See xpose.plot.bw
for details.
See also
xpose.plot.bw
, xpose.panel.bw
,
bwplot
, 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.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()
,
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
if (FALSE) {
## We expect to find the required NONMEM run and table files for run
## 5 in the current working directory
xpdb5 <- xpose.data(5)
## Here we load the example xpose database
data(simpraz.xpdb)
xpdb <- simpraz.xpdb
## A vanilla plot
absval.wres.vs.cov.bw(xpdb)
## A custom plot
absval.wres.vs.cov.bw(xpdb, bwdotcol="white",
bwdotpch=15,
bwreccol="red",
bwrecfill="red",
bwumbcol="red",
bwoutpch=5,
bwoutcol="black")
## A vanilla plot using IWRES
absval.iwres.vs.cov.bw(xpdb)
}