validationplot  R Documentation 
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 class '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(), ... )
object 
an 
val.type 
character. What type of validation statistic to plot. 
estimate 
character. Which estimates of the statistic to calculate.
See 
newdata 
data frame. Optional new data used to calculate statistic. 
ncomp, comps 
integer vector. The model sizes to compute the statistic
for. See 
intercept 
logical. Whether estimates for a model with zero components should be calculated as well. 
... 
Further arguments sent to underlying plot functions. 
x 
an 
nCols, nRows 
integers. The number of coloumns and rows the plots will
be laid out in. If not specified, 
type 
character. What type of plots to create. Defaults to

lty 
vector of line types (recycled as neccessary). Line types can be
specified as integers or character strings (see 
lwd 
vector of positive numbers (recycled as neccessary), giving the width of the lines. 
pch 
plot character. A character string or a vector of single
characters or integers (recycled as neccessary). See 
cex 
numeric vector of character expansion sizes (recycled as neccessary) for the plotted symbols. 
col 
character or integer vector of colors for plotted lines and
symbols (recycled as neccessary). See 
legendpos 
Legend position. Optional. If present, a legend is drawn
at the given position. The position can be specified symbolically (e.g.,

xlab, ylab 
titles for x and y axes. Typically character
strings, but can be expressions (e.g., 
main 
optional main title for the plot. See Details. 
ask 
logical. Whether to ask the user before each page of a plot. 
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 nonstandard 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.)
legend
has many options. If you want greater control
over the appearance of the legend, omit the legendpos
argument and
call legend
manually.
Ron Wehrens and BjørnHelge Mevik
mvr
, plot.mvr
, RMSEP
,
MSEP
, R2
, matplot
,
legend
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 ## End(Not run)
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