xpose4: absval_delta_vs_cov_model_comp – R documentation

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absval_delta_vs_cov_model_comp

Model comparison plots, of absolute differences in goodness-of-fit predictors against covariates, for Xpose 4

Description

These functions plot absolute differences in PRED, IPRED, WRES, CWRES and IWRES against covariates for two specified model fits.

Usage

absval.dcwres.vs.cov.model.comp(
  object,
  object.ref = NULL,
  type = NULL,
  ylb = expression(paste("|", Delta, "CWRES|")),
  main = "Default",
  ...
)

absval.dipred.vs.cov.model.comp(
  object,
  object.ref = NULL,
  type = NULL,
  ylb = expression(paste("|", Delta, "IPRED|")),
  main = "Default",
  ...
)

absval.diwres.vs.cov.model.comp(
  object,
  object.ref = NULL,
  type = NULL,
  ylb = expression(paste("|", Delta, "IWRES|")),
  main = "Default",
  ...
)

absval.dpred.vs.cov.model.comp(
  object,
  object.ref = NULL,
  type = NULL,
  ylb = expression(paste("|", Delta, "PRED|")),
  main = "Default",
  ...
)

absval.dwres.vs.cov.model.comp(
  object,
  object.ref = NULL,
  type = NULL,
  ylb = expression(paste("|", Delta, "WRES|")),
  main = "Default",
  ...
)

Arguments

`object`	An xpose.data object.
`object.ref`	An xpose.data object. If not supplied, the user will be prompted.
`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.
`ylb`	A string giving the label for the y-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"` or `NULL` for no plot title.
`...`	Other arguments passed to `link{xpose.plot.default}`.

Details

Conditional weighted residuals (CWRES) may 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.

Functions

absval.dcwres.vs.cov.model.comp: The absolute differences in individual predictions against covariates for two specified model fits.
absval.dipred.vs.cov.model.comp: The absolute differences in individual predictions against covariates for two specified model fits.
absval.diwres.vs.cov.model.comp: The absolute differences in individual weighted residuals against covariates for two specified model fits.
absval.dpred.vs.cov.model.comp: The absolute differences in population predictions against covariates for two specified model fits.
absval.dwres.vs.cov.model.comp: The absolute differences in population weighted residuals against covariates for two specified model fits.

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(), 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.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 basic dWRES plot, without prompts
absval.dwres.vs.cov.model.comp(xpdb5, xpdb6)

## Custom colours and symbols, no user IDs
absval.dpred.vs.cov.model.comp(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