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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.


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



An object.


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


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.


Should we use log transformations in the plots?


Other arguments passed to xpose.plot.default.


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).


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,

Other specific functions:, absval.cwres.vs.pred(),, absval.iwres.cwres.vs.ipred.pred(),, absval.iwres.vs.idv(), absval.iwres.vs.ipred(),, absval.iwres.vs.pred(),, absval.wres.vs.idv(), absval.wres.vs.pred(),, absval_delta_vs_cov_model_comp, addit.gof(), autocorr.cwres(), autocorr.iwres(), autocorr.wres(), basic.model.comp(),, cat.pc(), cov.splom(), cwres.dist.hist(), cwres.dist.qq(), cwres.vs.cov(), cwres.vs.idv(),, cwres.vs.pred(),, cwres.wres.vs.idv(), cwres.wres.vs.pred(), dOFV.vs.cov(),, dOFV1.vs.dOFV2(), data.checkout(), dv.preds.vs.idv(), dv.vs.idv(), dv.vs.ipred(),,, dv.vs.pred(),,, 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.pred(),, xpose.VPC(), xpose.VPC.both(), xpose.VPC.categorical(), xpose4-package


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