ggindplot: Individual factor map for 'rpca' using 'ggplot'.

In rsvd: Randomized Singular Value Decomposition

Description

Creates a pretty plot which is showing the individual factor map, i.e, plotting the principal component scores.

Usage

ggindplot(
  rpcaObj,
  pcs = c(1, 2),
  groups = NULL,
  alpha = 0.6,
  ellipse = TRUE,
  alpha.ellipse = 0.2,
  ind_labels = TRUE,
  ind_labels.names = NULL
)

Arguments

rpcaObj	Object returned by the rpca function.
pcs	Array_like. An array with two values indicating the two PCs which should be used for plotting. By default the first two PCs are used, e.g., c(1,2).
groups	Factor, optional. Factor indicating groups.
alpha	Scalar, optional. Alpha transparency for scatter plot.
ellipse	Bool (TRUE, FALSE), optional. Draw a 1sd data ellipse for each group, if TRUE.
alpha.ellipse	Scalar, optional. Alpha transparency for ellipse.
ind_labels	Bool (TRUE, FALSE), optional. Plot names for each individual point, if TRUE.
ind_labels.names	Array_like, optional. User specific labels for the individual points.

Author(s)

N. Benjamin Erichson, [e-mail]

See Also

rpca, ggplot

Examples

#See ?rpca

Example output

rsvd documentation built on April 16, 2021, 9:06 a.m.