absval.wres.vs.idv | R Documentation |
This is a plot of the absolute value of the CWRES (default, other residuals
as an option) vs independent variable, 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 the xpose.data
object but may be overridden by supplying them as arguments.
absval.wres.vs.idv(
object,
idv = "idv",
wres = "Default",
ylb = "Default",
smooth = TRUE,
idsdir = "up",
type = "p",
...
)
object |
An xpose.data object. |
idv |
the independent variable. |
wres |
Which weighted residual to use. |
ylb |
Y-axis label. |
smooth |
Logical value indicating whether an x-y smooth should be superimposed. The default is TRUE. |
idsdir |
Direction for displaying point labels. The default is "up", since we are displaying absolute values. |
type |
Type of plot. The default is points only ("p"), but lines ("l") and both ("b") are also available. |
... |
Other arguments passed to |
A wide array of extra options controlling xyplots are available. See
xpose.plot.default
for details.
Returns an xyplot of |CWRES| vs idv (often TIME, defined by
xvardef
).
Andrew Hooker
xpose.plot.default
,
xpose.panel.default
, xyplot
,
xpose.prefs-class
, compute.cwres
,
xpose.data-class
help
, ~~~
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.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
## Not run:
## We expect to find the required NONMEM run and table files for run
## 5 in the current working directory
xpdb5 <- xpose.data(5)
## End(Not run)
## Here we load the example xpose database
data(simpraz.xpdb)
xpdb <- simpraz.xpdb
## A vanilla plot
absval.wres.vs.idv(xpdb)
## A conditioning plot
absval.wres.vs.idv(xpdb, by="HCTZ")
## Custom heading and axis labels
absval.wres.vs.idv(xpdb, main="Hello World", ylb="|CWRES|", xlb="IDV")
## Custom colours and symbols
absval.wres.vs.idv(xpdb, cex=0.6, pch=3, col=1)
## using the NPDEs instead of CWRES
absval.wres.vs.idv(xpdb,wres="NPDE")
## subsets
absval.wres.vs.idv(xpdb,subset="TIME<10")
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