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addit.gof

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 "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

Plot the WRES even if other residuals are available.

...

Other arguments passed to link{xpose.plot.default}.

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

Examples

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

## A vanilla plot
addit.gof(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

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