Functions to plot validation statistics, such as RMSEP or \(R^2\), as a function of the number of components.
validationplot(object, val.type = c("RMSEP", "MSEP", "R2"), estimate,
newdata, ncomp, comps, intercept, …)
# S3 method for mvrVal
plot(x, nCols, nRows, type = "l", lty = 1:nEst,
lwd = par("lwd"), pch = 1:nEst, cex = 1, col = 1:nEst, legendpos,
xlab = "number of components", ylab = x$type, main,
ask = nRows * nCols < nResp && dev.interactive(), …)an mvr object.
character. What type of validation statistic to plot.
character. Which estimates of the statistic to
calculate. See RMSEP.
data frame. Optional new data used to calculate statistic.
integer vector. The model sizes to compute the statistic
for. See RMSEP.
logical. Whether estimates for a model with zero components should be calculated as well.
integers. The number of coloumns and rows the
plots will be laid out in. If not specified, plot.mvrVal tries
to be intelligent.
character. What type of plots to create. Defaults to
"l" (lines). Alternative types include "p" (points)
and "b" (both). See plot for a complete list
of types.
vector of line types (recycled as neccessary). Line types can be
specified as integers or character strings (see par
for the details).
vector of positive numbers (recycled as neccessary), giving the width of the lines.
plot character. A character string or a vector of
single characters or integers (recycled as neccessary). See
points for all alternatives.
numeric vector of character expansion sizes (recycled as neccessary) for the plotted symbols.
character or integer vector of colors for plotted lines and
symbols (recycled as neccessary). See par for the details.
Legend position. Optional. If present, a legend is
drawn at the given position. The position can be specified
symbolically (e.g., legendpos = "topright"). This requires
R >= 2.1.0. Alternatively, the position can be specified
explicitly (legendpos = t(c(x,y))) or interactively
(legendpos = locator()). This only works well for
plots of single-response models.
titles for \(x\) and \(y\) axes. Typically
character strings, but can be expressions (e.g.,
expression(R^2) or lists. See title for details.
optional main title for the plot. See Details.
logical. Whether to ask the user before each page of a plot.
Further arguments sent to underlying plot functions.
validationplot calls the proper validation function (currently
MSEP, RMSEP or R2) and plots
the results with plot.mvrVal. validationplot can be
called through the mvr plot method, by specifying
plottype = "validation".
plot.mvrVal creates one plot for each response variable in the
model, laid out in a rectangle. It uses matplot for
performing the actual plotting. If legendpos is given, a
legend is drawn at the given position.
The argument main can be used to specify the main title of the
plot. It is handled in a non-standard way. If there is only on (sub)
plot, main will be used as the main title of the plot. If
there is more than one (sub) plot, however, the presence of
main will produce a corresponding ‘global’ title on the
page. Any graphical parametres, e.g., cex.main, supplied to
coefplot will only affect the ‘ordinary’ plot titles,
not the ‘global’ one. Its appearance can be changed by setting
the parameters with par, which will affect both
titles. (To have different settings for the two titles, one can
override the par settings with arguments to the plot function.)
# NOT RUN {
data(oliveoil)
mod <- plsr(sensory ~ chemical, data = oliveoil, validation = "LOO")
# }
# NOT RUN {
## These three are equivalent:
validationplot(mod, estimate = "all")
plot(mod, "validation", estimate = "all")
plot(RMSEP(mod, estimate = "all"))
## Plot R2:
plot(mod, "validation", val.type = "R2")
## Plot R2, with a legend:
plot(mod, "validation", val.type = "MSEP", legendpos = "top") # R >= 2.1.0
# }
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