Functions to make scatter plots of scores or correlation loadings, and scatter or line plots of loadings.
scoreplot(object, ...) ## Default S3 method: scoreplot( object, comps = 1:2, labels, identify = FALSE, type = "p", xlab, ylab, ... ) ## S3 method for class 'scores' plot(x, ...) loadingplot(object, ...) ## Default S3 method: 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, ... ) ## S3 method for class 'loadings' plot(x, ...) corrplot( object, comps = 1:2, labels, plotx = TRUE, ploty = FALSE, radii = c(sqrt(1/2), 1), identify = FALSE, type = "p", xlab, ylab, col, ... )
an object. The fitted model.
further arguments sent to the underlying plot function(s).
integer vector. The components to plot.
optional. Alternative plot labels or x axis labels. See Details.
logical. Whether to use
character. What type of plot to make. Defaults to
titles for x and y axes. Typically character
strings, but can be expressions or lists. See
logical. Whether the loadings should be plotted as a scatter instead of as lines.
vector of line types (recycled as neccessary). Line types can be
specified as integers or character strings (see
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
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
Legend position. Optional. Ignored if
optional vector of length two, with the x limits of the plot.
locical. Whether to plot the X correlation loadings.
locical. Whether to plot the Y correlation loadings.
numeric vector, giving the radii of the circles drawn in
plot.scores is simply a wrapper calling
scoreplot, passing all
arguments. Similarly for
scoreplot is generic, currently with a default method that works for
matrices and any object for which
scores returns a matrix.
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
TRUE, the function
identify is used to interactively identify points.
loadingplot is generic, with a default method that works for
matrices and any object where
loadings returns a matrix. If
TRUE, the default method works exactly like the
scoreplot method. Otherwise, it makes a lineplot of the
selected loading vectors, and if
identify to interactively identify points. Also, if
legendpos is given, a legend is drawn at the position indicated.
corrplot works exactly like the default
except that at least two components must be selected. The
“correlation loadings”, i.e. the correlations between each variable
and the selected components (see References), are plotted as pairwise
scatter plots, with concentric circles of radii given by
point corresponds to a 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. By default, only the correlation loadings of the
X variables are plotted, but if
TRUE, also the
Y correlation loadings are plotted.
corrplot can also be called
through the plot method for
mvr objects, by specifying
"correlation", respectively. See
labels can be a vector of labels or one of
If a scatter plot is produced (i.e.,
scatter = TRUE), the labels are used instead
of plot symbols for the points plotted. If
"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
"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.
pretty.xlabels is only used when
specified for a line plot. If
TRUE (default), the code tries to use
a ‘pretty’ selection of labels. If
"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.
The functions return whatever the underlying plot function (or
legend has many options. If you want greater control
over the appearance of the legend, omit the
legendpos argument and
Graphical parametres (such as
cex) can also be used
corrplot. They are not listed in the
argument list simply because they are not handled specifically in the
function (unlike in
loadingplot), but passed directly to the
underlying plot functions by
Tip: If the labels specified with
labels are too long, they get
clipped at the border of the plot region. This can be avoided by supplying
the graphical parameter
xpd = TRUE in the plot call.
The handling of
Ron Wehrens and Bjørn-Helge Mevik
Martens, H., Martens, M. (2000) Modified Jack-knife Estimation of Parameter Uncertainty in Bilinear Modelling by Partial Least Squares Regression (PLSR). Food Quality and Preference, 11(1–2), 5–16.
data(yarn) mod <- plsr(density ~ NIR, ncomp = 10, data = yarn) ## These three are equivalent: ## Not run: 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) ## End(Not run)
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