xpose4: basic.model.comp – R documentation

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basic.model.comp

Basic model comparison plots, for Xpose 4

Description

This creates a stack of four plots, comparing PRED, IPRED, WRES (or CWRES), and IWRES estimates for the two specified model fits.

Usage

basic.model.comp(
  object,
  object.ref = NULL,
  onlyfirst = FALSE,
  inclZeroWRES = FALSE,
  subset = xsubset(object),
  main = "Default",
  force.wres = FALSE,
  ...
)

Arguments

`object`	An xpose.data object.
`object.ref`	An xpose.data object. If not supplied, the user will be prompted.
`onlyfirst`	Logical value indicating whether only the first row per individual is included in the plot.
`inclZeroWRES`	Logical value indicating whether rows with WRES=0 is included in the plot. The default is TRUE.
`subset`	A string giving the subset expression to be applied to the data before plotting. See `xsubset`.
`main`	The title of the plot. If `"Default"` then a default title is plotted. Otherwise the value should be a string like `"my title"` or `NULL` for no plot title.
`force.wres`	Force function to use WRES?
`...`	Other arguments passed to `link{xpose.plot.default}`.

Details

Four basic model comparison plots are displayed in sequence.

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.

Value

Returns a stack of plots comprising comparisons of PRED, IPRED, WRES (or CWRES) and IWRES for the two specified runs.

Author(s)

E. Niclas Jonsson, Mats Karlsson, Andrew Hooker & Justin Wilkins

Other specific functions: absval.cwres.vs.cov.bw(), absval.cwres.vs.pred.by.cov(), absval.cwres.vs.pred(), absval.iwres.cwres.vs.ipred.pred(), absval.iwres.vs.cov.bw(), absval.iwres.vs.idv(), absval.iwres.vs.ipred.by.cov(), absval.iwres.vs.ipred(), absval.iwres.vs.pred(), absval.wres.vs.cov.bw(), absval.wres.vs.idv(), absval.wres.vs.pred.by.cov(), absval.wres.vs.pred(), absval_delta_vs_cov_model_comp, addit.gof(), autocorr.cwres(), autocorr.iwres(), autocorr.wres(), basic.gof(), cat.dv.vs.idv.sb(), cat.pc(), cov.splom(), cwres.dist.hist(), cwres.dist.qq(), cwres.vs.cov(), cwres.vs.idv.bw(), cwres.vs.idv(), cwres.vs.pred.bw(), cwres.vs.pred(), 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.by.cov(), dv.vs.ipred.by.idv(), dv.vs.ipred(), dv.vs.pred.by.cov(), dv.vs.pred.by.idv(), dv.vs.pred.ipred(), dv.vs.pred(), gof(), ind.plots.cwres.hist(), ind.plots.cwres.qq(), ind.plots(), 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.bw(), wres.vs.idv(), wres.vs.pred.bw(), wres.vs.pred(), xpose.VPC.both(), xpose.VPC.categorical(), xpose.VPC(), xpose4-package

Examples

## Not run: 
## We expect to find the required NONMEM run and table files for runs
## 5 and 6 in the current working directory
xpdb5 <- xpose.data(5)
xpdb6 <- xpose.data(6)

## A vanilla plot, without prompts
basic.model.comp(xpdb5, xpdb6, prompt = FALSE)

## Custom colours and symbols, no user IDs
basic.model.comp.cwres(xpdb5, xpdb6, cex=0.6, pch=8, col=1, ids=NULL)

## End(Not run)

xpose4

Diagnostics for Nonlinear Mixed-Effect Models

v4.7.1

LGPL (>= 3)

Authors

Andrew C. Hooker [aut, cre, cph], Mats O. Karlsson [aut, cph], Justin J. Wilkins [aut], E. Niclas Jonsson [aut, trl, cph], Ron Keizer [ctb] (functionality for bootstrap of GAM and SCM)

Initial release