Display observations in a plane defined by two retained
principal components from rpca. Each point shows an
observation's fitted scores, allowing patterns in the selected components
to be compared across observations or supplied groups. Labels and group
ellipses can be added. The optional ggplot2 package is required.
ggindplot(
rpcaObj,
pcs = c(1, 2),
groups = NULL,
alpha = 0.6,
ellipse = TRUE,
alpha.ellipse = 0.2,
ind_labels = TRUE,
ind_labels.names = NULL
)A ggplot2 plot object. Print the object to draw the plot, or add layers, labels, and themes with ggplot2.
An object returned by rpca, with
real-valued scores. Complex factor maps are not supported. Fit with
retx = TRUE so that rpcaObj$x is available.
Integer vector of length two selecting the retained principal
components to plot, in horizontal and vertical order. The default is
c(1, 2). Both indices must be finite integers within the retained
component range.
Optional factor with one entry for each row of rpcaObj$x,
in the same order. The length must match the number of score rows;
shorter inputs are not recycled. Groups control point colours and, when
requested, ellipses. The default, NULL, uses one colour and draws
no ellipse.
If rpca omitted incomplete observations, supply groups for the
retained rows only.
Numeric value between zero and one controlling point
transparency, with zero fully transparent and one opaque. The default is
0.6.
Logical; draw a filled data ellipse for each supplied group
when TRUE (the default). The defaults of
stat_ellipse give a multivariate-t ellipse at
level 0.95. See Details for its interpretation.
Numeric value between zero and one controlling ellipse
transparency. The default is 0.2; ignored when no ellipse is drawn.
Logical; show a text label for each observation when
TRUE (the default). Set to FALSE to reduce clutter.
Optional character vector with one label per row of
rpcaObj$x, in the same order. By default, the score row names are
used, or sequential row numbers when names are absent. Labels are displayed
only when ind_labels = TRUE.
N. Benjamin Erichson
The horizontal and vertical coordinates are the columns of
rpcaObj$x selected by pcs. These fitted scores retain the
centering and scaling used in rpca; the plotting function does not
standardize or recompute them. For randomized fits, they are the stored
projected-SVD scores described in rpca.
Each axis label gives its component's share of rpcaObj$var, the
total variance of the processed input. Variance in omitted components
remains in the denominator, so a view of two components need not account
for all of the variation.
When groups are supplied, point colours identify group membership and
data ellipses summarize the spread of fitted scores within each group.
The ellipses use the multivariate-t model in
stat_ellipse, whose computation also requires
the recommended package MASS. They do not estimate confidence
regions for group means or test group separation. Small groups or
degenerate score distributions may not support ellipse estimation; use
ellipse = FALSE in that case.
rpca, ggbiplot,
ggcorplot, ggscreeplot,
ggplot, stat_ellipse
if (requireNamespace("ggplot2", quietly = TRUE)) {
set.seed(42)
fit <- rpca(iris[, 1:4], k = 3)
print(ggindplot(fit, pcs = c(1, 3), groups = iris$Species,
ellipse = FALSE, ind_labels = FALSE))
}
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