nlme.vpcplot: Plot a VPC of an nlme object

In qPharmetra/qpToolkit: qPharmetra R Tools

Plot a VPC of an nlme object

Description

Plot a VPC of an nlme object

Usage

## S3 method for class 'vpcplot'
nlme(
  object,
  vpc,
  formula,
  obsData = NULL,
  xLabel,
  yLabel,
  xLimits,
  yLimits,
  logY = FALSE,
  color.style = list(observed = rgb(0.2, 0.2, 0.2), central = blue[10], inner = blue[4],
    outer = blue[1]),
  symbol = list(pch = 15, cex = 0.5),
  aspect = 1,
  cex.label = 1.5,
  nx = NULL,
  showPredAs = "area",
  showObsDots = TRUE,
  showObsLines = TRUE,
  obscol.dot = gray[8],
  obscex.dot = 0.5,
  obspch.dot = 1,
  obscol.line = gray[10],
  predcol.central = blue[6],
  predcol.outer = blue[7],
  predcol.area = blue[1],
  predcol.inner = blue[3],
  ...
)

Arguments

object	the nlme object (if it's an nlme.run object the input should read object$object)
vpc	the output from nlme.vpc
formula	a formula detailing what to plot
obsData	the observation data, if not supplied defaults to obsData = getData(object). Use if newdata in extract.nlme was specified
xLabel	same as xlab
yLabel	same as ylab
xLimits	same as xlim
yLimits	same as ylim
logY	logical to log Y axis
color.style	list with layout options, such as:
symbol	list with elements pch (15) and cex (0.5)
aspect	trellis banking value (defaults to 1 for sqaure panels)
cex.label	tex size for x and y labels (1.5)
nx	number of bins for x covariate
showPredAs	layout style (defaults to "area" for polygons but could be 'lines' too).
showObsDots	logical to showobserved dots (T)
showObsLines	logical to show quantile lines of observed (T)
obscol.dot	color of observed dot
obscex.dot	symbol size
obspch.dot	type of symbol
obscol.line	observed line color
predcol.central	predicted central tendency color
predcol.outer	predicted outer polygon color
predcol.area	predicted overall polygon color
predcol.inner	predicted inner polygon (IQR) color
...	any additional arguments passed on to the lattice call

Value

A VPC plot.

See Also

nlme.vpc, nlme.extract

Examples

# library(nlme)
pkpdData = example.pkpdData()
EFF.1comp.1abs <- function(dose, tob, cl, v, ka, keo)
 {
   # Effect-site concentration for 1-compartment model, 1st-order absorption

   kel = cl / v

   # Define coefficients
   A = 1/(kel-ka) / (keo-ka)
   B = 1/(ka-kel) / (keo-kel)
   C = 1/(ka-keo) / (kel-keo)

   # Return effect-site concentration
   dose*ka*keo/v * (A*exp(-ka*tob) + B*exp(-kel*tob) + C*exp(-keo*tob))
 }
 fit.PD004.nlme = nlme.run(
   model = value ~ base + EFF.1comp.1abs(dose, time, cl * exp(cl.eta), v, ka, keo),
   data = pkpdData[pkpdData$type == "PD" & pkpdData$dose > 0 & pkpdData$value > 0.5, ],
   fixed = base + cl + v + ka + keo ~ 1,
   random = cl.eta ~ 1,
   groups = ~ id,
   start = c(base = 1, cl = 1, v = 10, ka = 1, keo = 0.01),
   problem = "True Model",
   reference = 4)
 summary(fit.PD004.nlme$object)
 nlme.extract(fit.PD004.nlme$object)$table
 vpc.PD004.nlme = nlme.vpc(fit.PD004.nlme$object, nrep = 100)
 nlme.vpcplot(fit.PD004.nlme$object, vpc.PD004.nlme)

qPharmetra/qpToolkit documentation built on May 24, 2023, 8:52 a.m.