Histograms of weighted residuals for each individual in an Xpose data object, for Xpose 4

This is a compound plot consisting of histograms of the distribution of weighted residuals (any weighted residual available from NONMEM) for every individual in the dataset. It is a wrapper encapsulating arguments to the xpose.plot.histogram function.

Usage

ind.plots.cwres.hist(object, wres = "cwres", ...)

ind.plots.wres.hist(
  object,
  main = "Default",
  wres = "wres",
  ylb = NULL,
  layout = c(4, 4),
  inclZeroWRES = FALSE,
  subset = xsubset(object),
  scales = list(cex = 0.7, tck = 0.5),
  aspect = "fill",
  force.by.factor = TRUE,
  ids = F,
  as.table = TRUE,
  hicol = object@Prefs@Graph.prefs$hicol,
  hilty = object@Prefs@Graph.prefs$hilty,
  hilwd = object@Prefs@Graph.prefs$hilwd,
  hidcol = object@Prefs@Graph.prefs$hidcol,
  hidlty = object@Prefs@Graph.prefs$hidlty,
  hidlwd = object@Prefs@Graph.prefs$hidlwd,
  hiborder = object@Prefs@Graph.prefs$hiborder,
  prompt = FALSE,
  mirror = NULL,
  main.cex = 0.9,
  max.plots.per.page = 1,
  ...
)

Arguments

object: An xpose.data object.
wres: Which weighted residual should we plot? Defaults to the WRES.
...: Other arguments passed to xpose.plot.histogram.
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.
ylb: A string giving the label for the y-axis. NULL if none.
layout: A list giving the layout of the graphs on the plot, in columns and rows. The default is 4x4.
inclZeroWRES: Logical value indicating whether rows with WRES=0 is included in the plot. The default is FALSE.
subset: A string giving the subset expression to be applied to the data before plotting. See xsubset.
scales: see xpose.plot.histogram
aspect: see xpose.plot.histogram
force.by.factor: see xpose.plot.histogram
ids: see xpose.plot.histogram
as.table: see xpose.plot.histogram
hicol: the fill colour of the histogram - an integer or string. The default is blue (see histogram).
hilty: the border line type of the histogram - an integer. The default is 1 (see histogram).
hilwd: the border line width of the histogram - an integer. The default is 1 (see histogram).
hidcol: the fill colour of the density line - an integer or string. The default is black (see histogram).
hidlty: the border line type of the density line - an integer. The default is 1 (see histogram).
hidlwd: the border line width of the density line - an integer. The default is 1 (see histogram).
hiborder: the border colour of the histogram - an integer or string. The default is black (see histogram).
prompt: Specifies whether or not the user should be prompted to press RETURN between plot pages. Default is FALSE.
mirror: Mirror plots are not yet implemented in this function and this argument must contain a value of NULL
main.cex: The size of the title.
max.plots.per.page: Maximum number of plots per page

Value

Returns a compound plot comprising histograms of weighted residual conditioned on individual.

Details

Matrices of histograms of weighted residuals in each included individual are displayed. ind.plots.cwres.hist is just a wrapper for ind.plots.wres.hist(object,wres="cwres").

Functions

ind.plots.cwres.hist(): Histograms of conditional weighted residuals for each individual

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.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(), 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.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

Author

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

Examples

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

## A plot of the first 16 individuals
ind.plots.cwres.hist(xpdb, subset="ID<18")