selectPlot: Selection plot

In rospca: Robust Sparse PCA using the ROSPCA Algorithm

Description

Plot Information Criterion (IC) versus values of the sparsity parameter λ.

Usage

selectPlot(sl, indicate = TRUE, main = NULL)

Arguments

sl	Output from selectLambda function.
indicate	Logical indicating if the value of λ corresponding to the minimal IC is indicated on the plot, default is TRUE.
main	Title for the plot, default is NULL (no title).

Author(s)

Tom Reynkens

References

Hubert, M., Reynkens, T., Schmitt, E. and Verdonck, T. (2016). “Sparse PCA for High-Dimensional Data with Outliers,” Technometrics, 58, 424–434.

See Also

selectLambda

Examples

X <- dataGen(m=1, n=100, p=10, eps=0.2, bLength=4)$data[[1]]

sl <- selectLambda(X, k=2, method="ROSPCA", lstep=0.1)
selectPlot(sl)

Example output

rospca documentation built on May 2, 2019, 1:42 p.m.