xpose4: absval.iwres.cwres.vs.ipred.pred – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

absval.iwres.cwres.vs.ipred.pred

Absolute population weighted residuals vs population predictions, and absolute individual weighted residuals vs individual predictions, for Xpose 4

Description

This is a matrix plot of absolute population weighted residuals (|CWRES|) vs population predictions (PRED) and absolute individual weighted residuals (|IWRES|) vs individual predictions (IPRED), a specific function in Xpose 4. It is a wrapper encapsulating arguments to the absval.cwres.vs.pred and absval.iwres.vs.ipred functions.

Usage

absval.iwres.cwres.vs.ipred.pred(object, main = "Default", ...)

absval.iwres.wres.vs.ipred.pred(object, main = "Default", ...)

Arguments

`object`	An xpose.data object.
`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

The plots created by the absval.wres.vs.pred and absval.iwres.vs.ipred functions are presented side by side for comparison.

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

Value

Returns a compound plot.

Functions

absval.iwres.wres.vs.ipred.pred: absolute population weighted residuals (|WRES|) vs population predictions (PRED) and absolute individual weighted residuals (|IWRES|) vs individual predictions (IPRED)

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.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.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

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

## A vanilla plot
absval.iwres.wres.vs.ipred.pred(xpdb)
absval.iwres.cwres.vs.ipred.pred(xpdb)

## Custom colours and symbols
absval.iwres.cwres.vs.ipred.pred(xpdb, cex=0.6, pch=8, col=1)

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