dOFV.vs.id: Change in Objective function value vs. removal of...

Description Usage Arguments Author(s) See Also Examples

View source: R/dOFV.vs.id.R

Description

A plot showing the most and least influential individuals in determining a drop in OFV between two models.

Usage

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dOFV.vs.id(xpdb1, xpdb2, sig.drop = -3.84, decrease.label.number = 3,
  increase.label.number = 3, id.lab.cex = 0.6, id.lab.pos = 2,
  type = "o", xlb = "Number of subjects removed",
  ylb = expression(paste(Delta, "OFV")), main = "Default",
  sig.line.col = "red", sig.line.lty = "dotted", tot.line.col = "grey",
  tot.line.lty = "dashed", key = list(columns = 1, lines = list(pch =
  c(super.sym$pch[1:2], NA, NA), type = list("o", "o", "l", "l"), col =
  c(super.sym$col[1:2], sig.line.col, tot.line.col), lty = c(super.sym$lty[1:2],
  sig.line.lty, tot.line.lty)), text = list(c(expression(paste(Delta, OFV[i] <
  0)), expression(paste(Delta, OFV[i] > 0)), expression(paste("Significant  ",
  Delta, OFV)), expression(paste("Total  ", Delta, OFV)))), corner = c(0.95,
  0.5), border = T), ...)

Arguments

xpdb1

Xpose data object for first NONMEM run ("new" run)

xpdb2

Xpose data object for Second NONMEM run ("reference" run)

sig.drop

What is a significant drop of OFV?

decrease.label.number

How many points should bw labeled with ID values for those IDs with a drop in iOFV?

increase.label.number

How many points should bw labeled with ID values for those IDs with an increase in iOFV?

id.lab.cex

Size of ID labels.

id.lab.pos

ID label position.

type

Type of lines.

xlb

X-axis label.

ylb

Y-axis label.

main

Title of plot.

sig.line.col

Significant OFV drop line color.

sig.line.lty

Significant OFV drop line type.

tot.line.col

Total OFV drop line color.

tot.line.lty

Total OFV drop line type.

key

Legend for plot.

...

Additional arguments to function.

Author(s)

Andrew C. Hooker

See Also

Other specific functions: absval.cwres.vs.cov.bw, absval.cwres.vs.pred.by.cov, absval.cwres.vs.pred, absval.iwres.cwres.vs.ipred.pred, absval.iwres.vs.cov.bw, absval.iwres.vs.idv, absval.iwres.vs.ipred.by.cov, absval.iwres.vs.ipred, absval.iwres.vs.pred, absval.wres.vs.cov.bw, absval.wres.vs.idv, absval.wres.vs.pred.by.cov, absval.wres.vs.pred, 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.bw, cwres.vs.idv, cwres.vs.pred.bw, cwres.vs.pred, cwres_wres_vs_x, dOFV.vs.cov, dOFV1.vs.dOFV2, data.checkout, dv.preds.vs.idv, dv.vs.idv, dv.vs.ipred.by.cov, dv.vs.ipred.by.idv, dv.vs.ipred, dv.vs.pred.by.cov, dv.vs.pred.by.idv, dv.vs.pred.ipred, dv.vs.pred, gof, ind.plots.cwres.hist, ind.plots.cwres.qq, ind.plots, 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.bw, wres.vs.idv, wres.vs.pred.bw, wres.vs.pred, xpose.VPC.both, xpose.VPC.categorical, xpose.VPC, xpose4-package

Examples

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## Not run: 
library(xpose4)

## first make sure that the iofv values are read into xpose
cur.dir <- getwd()
setwd(paste(cur.dir,"/LAG_TIME",sep=""))
xpdb1 <- xpose.data(1)
setwd(paste(cur.dir,"/TRANSIT_MODEL",sep=""))
xpdb2 <- xpose.data(1)
setwd(cur.dir)

## then make the plot
dOFV.vs.id(xpdb1,xpdb2)

## End(Not run)

UUPharmacometrics/xpose4 documentation built on April 3, 2018, 12:05 p.m.