rsvd: ggcorplot – R documentation

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ggcorplot

Variables factor map for rpca using ggplot.

Creates a pretty plot which is showing the correlation of the original variable with the principal component (PCs).

ggcorplot(
  rpcaObj,
  pcs = c(1, 2),
  loadings = TRUE,
  var_labels = FALSE,
  var_labels.names = NULL,
  alpha = 1,
  top.n = NULL
)

`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))*.
`var_labels`	Bool (TRUE, FALSE), optional. Plot variable names, if TRUE.
`var_labels.names`	Array_like, optional. User specific labels for the variables
`alpha`	Scalar, optional. Alpha transparency of the arrows.
`top.n`	Scalar, optional. Number of (most influencial) variables to label with small circles.

N. Benjamin Erichson, erichson@berkeley.edu

Randomized Singular Value Decomposition

v1.0.5

GPL (>= 3)

Authors

N. Benjamin Erichson [aut, cre]

Initial release

2021-04-11