mcr (version 1.2.1)

MCResult.plotResiduals: Plot Residuals of an MCResult Object

Description

Plot Residuals of an MCResult Object

Usage

MCResult.plotResiduals(.Object, res.type = c("optimized", "y", "x"),
  xaxis = c("yhat", "both", "xhat"), ref.line = TRUE,
  ref.line.col = "red", ref.line.lty = 2, ref.line.lwd = 1, main = NULL,
  xlab = NULL, ylab = NULL, add.grid = TRUE, ...)

Arguments

.Object

object of type "MCResult".

res.type

If res.type="y" the difference between the test method and it's prediction will be drawn. If res.type="x" the reference method and it's prediction will be drawn. In case ordinary and weighted ordinary linear regression this difference will be zero.

xaxis

Values on the x-axis. One can choose from estimated values of x (xaxis="xhat"), y (xaxis="xhat") or the mean of estimated values of x and y (xaxis="both"). If res.type="optimized" the proper type of residuals for each regression will be drawn.

ref.line

logical value. If ref.line = TRUE (default), the reference line will be drawn.

ref.line.col

reference line color.

ref.line.lty

reference line type.

ref.line.lwd

reference line width.

xlab

label for the x-axis

ylab

label for the y-axis

add.grid

logical value. If add.grid = TRUE (default) the gridlines will be drawn.

main

character string specifying the main title of the plot

...

further graphical parameters

See Also

getResiduals, plot.mcr, plotDifference, plotBias, compareFit

Examples

# NOT RUN {
data(creatinine,package="mcr")
    x <- creatinine$serum.crea
    y <- creatinine$plasma.crea

    # Deming regression fit.
    # The confidence intercals for regression coefficients
    # are calculated with analytical method
    model <- mcreg( x,y,error.ratio=1,method.reg="WDeming", method.ci="jackknife",
                     mref.name = "serum.crea", mtest.name = "plasma.crea", na.rm=TRUE )
    plotResiduals(model, res.type="optimized", xaxis="both" )
    plotResiduals(model, res.type="y", xaxis="yhat")
# }