MCResult.plotResiduals | R Documentation |
Plot Residuals of an MCResult Object
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,
...
)
.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= |
ref.line |
logical value. If |
ref.line.col |
reference line color. |
ref.line.lty |
reference line type. |
ref.line.lwd |
reference line width. |
main |
character string specifying the main title of the plot |
xlab |
label for the x-axis |
ylab |
label for the y-axis |
add.grid |
logical value. If |
... |
further graphical parameters |
No return value, instead a plot is generated
getResiduals
, plot.mcr
, plotDifference
, plotBias
, compareFit
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")
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