predplot {pls}R Documentation

Prediction Plots

Description

Functions to plot predicted values against measured values for a fitted model.

Usage

predplot(object, ...)
## Default S3 method:
predplot(object, ...)
## S3 method for class 'mvr':
predplot(object, ncomp = object$ncomp, which, newdata, nCols, 
         nRows, xlab = "measured", ylab = "predicted",
         ..., font.main = 1, cex.main = 1.1)
predplotXy(x, y, line = FALSE, main = "Prediction plot",
           xlab = "measured response", ylab = "predicted response",
           line.col = par("col"), line.lty = NULL, line.lwd = NULL, ...)

Arguments

object a fitted model.
ncomp integer vector. The model sizes (numbers of components) to use for prediction.
which character vector. Which types of predictions to plot. Should be a subset of c("train", "validation", "test"). If not specified, plot.mvr selects test set predictions if newdata is supplied, otherwise cross-validated predictions if the model has been cross-validated, otherwise fitted values from the calibration data.
newdata data frame. New data to predict.
nCols, nRows integer. The number of coloumns and rows the plots will be laid out in. If not specified, plot.mvr tries to be intelligent.
xlab,ylab titles for x and y axes. Typically character strings, but can be expressions or lists. See title for details.
font.main font to use for main title. See par for details.
cex.main numeric. The magnification to be used for main titles relative to the current size.
x numeric vector. The observed response values.
y numeric vector. The predicted response values.
line logical. Whether a target line should be drawn.
main character. Main title of plot.
line.col, line.lty, line.lwd character or numeric. The col, lty and lwd parametres for the target line. See par for details.
... further arguments sent to underlying plot functions.

Details

predplot is a generic function for plotting predicted versus measured response values, with default and mvr methods currently implemented. The default method is very simple, and doesn't handle multiple responses or new data.

The mvr method, handles multiple responses, model sizes and types of predictions by making one plot for each combination. It can also be called through the plot method for mvr, by specifying plottype = "prediction" (the default).

predplotXy is an internal function and is not meant for interactive use. It is called by the predplot methods, and its arguments, e.g, line, can be given in the predplot call.

Value

The functions invisibly returns a matrix with the (last) plotted data.

Note

The font.main and cex.main must be (completely) named. This is to avoid that any argument cex or font matches them.

Author(s)

Ron Wehrens and Bjørn-Helge Mevik

See Also

mvr, plot.mvr

Examples

data(NIR)
mod <- plsr(y ~ X, ncomp = 10, data = NIR[NIR$train,], validation = "CV")
## Not run: 
predplot(mod, ncomp = 1:6)
plot(mod, ncomp = 1:6) # Equivalent to the previous
## Both cross-validated and test set predictions:
predplot(mod, ncomp = 4:6, which = c("validation", "test"),
         newdata = NIR[!NIR$train,])
## End(Not run)

data(sensory)
mod.sens <- plsr(Quality ~ Panel, ncomp = 4, data = sensory)
## Not run: plot(mod.sens, ncomp = 2:4) # Several responses gives several plots

[Package pls version 1.2-0 Index]