xpose4 (version 4.7.3)

basic.gof: Basic goodness-of-fit plots, for Xpose 4

Description

This is a compound plot consisting of plots of observations (DV) vs population predictions (PRED), observations (DV) vs individual predictions (IPRED), absolute individual weighted residuals (|IWRES|) vs IPRED, and weighted population residuals (CWRES) vs independent variable (IDV), a specific function in Xpose 4. WRES are also supported. It is a wrapper encapsulating arguments to the dv.vs.pred, dv.vs.ipred, absval.iwres.vs.ipred and wres.vs.idv functions.

Usage

basic.gof(object, force.wres = FALSE, main = "Default", use.log = FALSE, ...)

Value

Returns a compound plot comprising plots of observations (DV) vs population predictions (PRED), DV vs individual predictions (IPRED), absolute individual weighted residuals (|IWRES|) vs IPRED, and weighted populations residuals (WRES) vs the independent variable (IDV).

Arguments

object

An xpose.data object.

force.wres

Should the plots use WRES? Values can be TRUE/FALSE. Otherwise the CWRES are used if present.

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.

use.log

Should we use log transformations in the plots?

...

Other arguments passed to xpose.plot.default.

Author

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

Details

Four basic goodness-of-fit plots are presented side by side for comparison.

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.

basic.gof.cwres is just a wrapper for basic.gof with use.cwres=TRUE.

See Also

dv.vs.pred, dv.vs.ipred, absval.iwres.vs.ipred, wres.vs.idv, cwres.vs.idv, xpose.plot.default, xpose.panel.default, xyplot, compute.cwres, xpose.prefs-class, xpose.data-class

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

Examples

basic.gof(simpraz.xpdb)