Xpose visual predictive check for categorical data.

Xpose visual predictive check for categorical data (binary, ordered categorical and count data).

Usage

xpose.VPC.categorical(
  vpc.info = "vpc_results.csv",
  vpctab = dir(pattern = "^vpctab")[1],
  object = NULL,
  subset = NULL,
  main = "Default",
  main.sub = "Default",
  main.sub.cex = 0.85,
  real.col = 4,
  real.lty = "b",
  real.cex = 1,
  real.lwd = 1,
  median.line = FALSE,
  median.col = "darkgrey",
  median.lty = 1,
  ci.lines = FALSE,
  ci.col = "blue",
  ci.lines.col = "darkblue",
  ci.lines.lty = 3,
  xlb = "Default",
  ylb = "Proportion of Total",
  force.x.continuous = FALSE,
  level.to.plot = NULL,
  max.plots.per.page = 1,
  rug = TRUE,
  rug.col = "orange",
  censored = FALSE,
  ...
)

Arguments

vpc.info: Name of PSN file to use. File will come from VPC command in PsN.
vpctab: Name of vpctab file produced from PsN.
object: Xpose data object.
subset: Subset of data to look at.
main: Title for plot.
main.sub: Used for names above each plot when using multiple plots. Should be a vector, e.g. c("title 1","title 2").
main.sub.cex: Size of main.sub
real.col: Color of real line.
real.lty: Real line type.
real.cex: Size of real line.
real.lwd: Width of real line.
median.line: Dray a median line?
median.col: Color of median line.
median.lty: median line type.
ci.lines: Lines marking confidence interval?
ci.col: Color of CI area.
ci.lines.col: Color of CI lines.
ci.lines.lty: Type of CI lines.
xlb: X-axis label. If other than "default"" passed directly to xyplot.
ylb: Y-axis label. Passed directly to xyplot.
force.x.continuous: For the x variable to be continuous.
level.to.plot: Which levels of the variable to plot. Smallest level is 1, largest is number_of_levels. For example, with 4 levels, the largest level would be 4, the smallest would be 1.
max.plots.per.page: The number of plots per page.
rug: Should there be markings on the plot showing where the intervals for the VPC are?
rug.col: Color of the rug.
censored: Is this censored data? Censored data can be both below and above the limit of quantification.
...: Additional information passed to function.

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.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(), xpose4-package

Other PsN functions: boot.hist(), bootscm.import(), npc.coverage(), randtest.hist(), read.npc.vpc.results(), read.vpctab(), xpose.VPC(), xpose.VPC.both(), xpose4-package

Author

Andrew C. Hooker

Examples


if (FALSE) {
library(xpose4)

## move to the directory where results from PsN
## are found
cur.dir <- getwd()
setwd(paste(cur.dir,"/binary/vpc_36",sep=""))

xpose.VPC.categorical(level.to.plot=1,max.plots.per.page=4)
xpose.VPC.categorical(level.to.plot=1,max.plots.per.page=4,by="DOSE")

## ordered categorical plots
setwd(paste(cur.dir,"/ordered_cat/vpc_45",sep=""))
xpose.VPC.categorical()


## count
setwd(paste(cur.dir,"/count/vpc65b",sep=""))
xpose.VPC.categorical()

setwd(paste(cur.dir,"/count/vpc65a",sep=""))
xpose.VPC.categorical()

}

Usage

Arguments

See also

Author

Examples