addit.gof {xpose4} | R Documentation |
Additional goodness-of-fit plots, for Xpose 4
Description
This is a compound plot consisting of plots of weighted population residuals
(WRES) vs population predictions (PRED), absolute individual weighted
residuals (|IWRES|) vs independent variable (IDV), WRES vs IDV, and weighted
population residuals vs log(IDV), a specific function in Xpose 4. It is a
wrapper encapsulating arguments to the wres.vs.pred
,
iwres.vs.idv
and wres.vs.idv
functions.
Usage
addit.gof(
object,
type = "p",
title.size = 0.02,
title.just = c("center", "top"),
main = "Default",
force.wres = FALSE,
...
)
Arguments
object |
An xpose.data object. |
type |
1-character string giving the type of plot desired. The following values are possible, for details, see 'plot': '"p"' for points, '"l"' for lines, '"o"' for over-plotted points and lines, '"b"', '"c"') for (empty if '"c"') points joined by lines, '"s"' and '"S"' for stair steps and '"h"' for histogram-like vertical lines. Finally, '"n"' does not produce any points or lines. |
title.size |
Amount, in a range of 0-1, of how much space the title should take up in the plot) |
title.just |
how the title should be justified |
main |
The title of the plot. If |
force.wres |
Plot the WRES even if other residuals are available. |
... |
Other arguments passed to |
Details
Four additional goodness-of-fit plots are presented side by side for comparison.
A wide array of extra options controlling xyplots are available. See
xpose.plot.default
and
xpose.multiple.plot.default
for details.
Value
Returns a compound plot comprising plots of weighted population residuals (WRES) vs population predictions (PRED), absolute individual weighted residuals (|IWRES|) vs independent variable (IDV), WRES vs IDV, and weighted population residuals vs log(IDV).
Author(s)
E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins
See Also
wres.vs.pred
, iwres.vs.idv
,
wres.vs.idv
, 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
,
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
## Here we load the example xpose database
xpdb <- simpraz.xpdb
## A vanilla plot
addit.gof(xpdb)