scoreplot(object, ...)
## S3 method for class 'default':
scoreplot(object, comps = 1:2, labels, identify = FALSE, type = "p",
xlab, ylab, \dots)
## S3 method for class 'scores':
plot(x, \dots)loadingplot(object, ...)
## S3 method for class 'default':
loadingplot(object, comps = 1:2, scatter = FALSE, labels,
identify = FALSE, type, lty, lwd = NULL, pch, cex = NULL,
col, legendpos, xlab, ylab, pretty.xlabels = TRUE, xlim, \dots)
## S3 method for class 'loadings':
plot(x, \dots)
corrplot(object, comps = 1:2, labels, radii = c(sqrt(1/2), 1),
identify = FALSE, type = "p", xlab, ylab, ...)
corrplot. The default radii represent 50% and 100%
explained variance of the $X$ variables by the chosen components.identify to
interactively identify points. See below."p" (points) for scatter plots and "l" (lines) for
line plots. See plot for a complete list
of types (not all types arpar
for the details).points for all alternatives.par for the details.scatter is
TRUE. If present, a legend is drawn at the given position.
The position can be specified symbolically (e.g., legendpos =
"topright"). This requires Rtitle for details.TRUE, loadingplot
tries to plot the $x$ labels more nicely. See Details.scores or loadings object. The scores or
loadings to plot.identify) returns.plot.scores is simply a wrapper calling scoreplot,
passing all arguments. Similarly for plot.loadings. scoreplot is generic, currently with a default method that
works for matrices and any object for which scores
returns a matrix. The default scoreplot method
makes one or more scatter plots of the scores,
depending on how many components are selected. If one or two
components are selected, and identify is TRUE, the
function identify is used to interactively identify
points.
Also loadingplot is generic, with a default method that works
for matrices and any object where loadings returns a
matrix. If scatter is TRUE, the default method works exactly
like the default scoreplot method. Otherwise, it makes a lineplot of the selected
loading vectors, and if identify is TRUE,
uses identify to interactively identify points. Also,
if legendpos is given, a legend is drawn at the position
indicated.
corrplot works exactly like the default scoreplot
method, except that at least two components must be selected. The
radii. Each
point corresponds to an $X$ variable. The squared distance
between the point and origin equals the fraction of the variance of the
variable explained by the components in the panel. The default
radii corresponds to 50% and 100% explained variance.
scoreplot, loadingplot and corrplot can also be
called through the plot method for mvr objects, by specifying
plottype as "scores", "loadings" or
"correlation", respectively. See plot.mvr.
The argument labels can be a vector of labels or one of
"names" and "numbers".
If a scatter plot is produced (i.e., scoreplot, corrplot, or
loadingplot with scatter = TRUE), the labels
are used instead of plot symbols for the points plotted. If
labels is "names" or "numbers", the row
names or row numbers of the matrix (scores, loadings or correlation
loadings) are used.
If a line plot is produced (i.e., loadingplot), the labels are
used as $x$ axis labels. If labels is "names" or
"numbers", the variable names are used as labels, the
difference being that with "numbers", the variable names are
converted to numbers, if possible. Variable names of the forms
"number" or "number text" (where the space is optional),
are handled.
The argument pretty.xlabels is only used when labels is
specified for a line plot. If TRUE (default), the code tries
to use a labels is
"numbers", it also uses the numerical values of the labels for
horisontal spacing. If one has excluded parts of the spectral
region, one might therefore want to use pretty.xlabels = FALSE.
mvr, plot.mvr,
scores, loadings, identify,
legenddata(yarn)
mod <- plsr(density ~ NIR, ncomp = 10, data = yarn)
## These three are equivalent:
scoreplot(mod, comps = 1:5)
plot(scores(mod), comps = 1:5)
plot(mod, plottype = "scores", comps = 1:5)
loadingplot(mod, comps = 1:5)
loadingplot(mod, comps = 1:5, legendpos = "topright") # With legend
loadingplot(mod, comps = 1:5, scatter = TRUE) # Plot as scatterplots
corrplot(mod, comps = 1:2)
corrplot(mod, comps = 1:3)Run the code above in your browser using DataLab