rsvd: ggbiplot – R documentation

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ggbiplot

Biplot for rpca using ggplot.

Description

Creates a pretty biplot which is showing the individual factor map overlayed by the variables factor map, i.e, plotting both the principal component scores and directions.

Usage

ggbiplot(
  rpcaObj,
  pcs = c(1, 2),
  loadings = TRUE,
  groups = NULL,
  alpha = 0.6,
  ellipse = TRUE,
  alpha.ellipse = 0.2,
  var_labels = TRUE,
  var_labels.names = NULL,
  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).
`loadings`	Bool (TRUE, FALSE), optional. If TRUE, the eigenvectors are unit scaled by the square root of the eigenvalues W = W diag(sqrt(eigvals))*.
`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.
`var_labels`	Bool (TRUE, FALSE), optional. Plot variable names, if TRUE.
`var_labels.names`	Array_like, optional. User specific labels for the individuals.
`ind_labels`	Bool (TRUE, FALSE), optional. Plot data point names, if TRUE.
`ind_labels.names`	Array_like, optional. User specific labels for data points.

Author(s)

N. Benjamin Erichson, erichson@berkeley.edu

Examples

#See ?rpca

rsvd

Randomized Singular Value Decomposition

v1.0.5

GPL (>= 3)

Authors

N. Benjamin Erichson [aut, cre]

Initial release

2021-04-11