xpose4: dv.preds.vs.idv – R documentation

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dv.preds.vs.idv

Observations (DV), individual predictions (IPRED) and population predictions (IPRED) plotted against the independent variable (IDV), for Xpose 4

Description

This is a compound plot consisting of plots of observations (DV), individual predictions (IPRED), and population predictions (PRED) against the independent variable (IDV), a specific function in Xpose 4. It is a wrapper encapsulating arguments to the xpose.plot.default function.

Usage

dv.preds.vs.idv(
  object,
  ylb = "Observations/Predictions",
  layout = c(3, 1),
  smooth = TRUE,
  scales = list(),
  ...
)

Arguments

`object`	An xpose.data object.
`ylb`	A string giving the label for the y-axis. `NULL` if none.
`layout`	A list controlling the number of columns and rows in a compound plot. The default is 2 columns and 1 row.
`smooth`	Logical value indicating whether an x-y smooth should be superimposed. The default is TRUE.
`scales`	A list to be used for the `scales` argument in `xyplot`.
`...`	Other arguments passed to `link{xpose.plot.default}`.

Details

A wide array of extra options controlling xyplots are available. See xpose.plot.default and xpose.panel.default for details.

Value

Returns a compound plot comprising plots of observations (DV), individual predictions (IPRED), and population predictions (PRED) against the independent variable (IDV).

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(), 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.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

## Here we load the example xpose database 
xpdb <- simpraz.xpdb

dv.preds.vs.idv(xpdb)

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