A wrapper which carries out sparse PCA analysis on a
Spectra object. The user can select various options for
scaling. There is no normalization by rows - do this manually using
normSpectra. The data will be centered, as is required by PCA.
s_pcaSpectra(spectra, choice = "noscale", K = 3, para = rep(0.5, K), ...)An object of S3 class Spectra().
A character string indicating the choice of scaling. One of
c("noscale", "autoscale", "Pareto"). "autoscale"
is called "standard normal variate" or "correlation matrix PCA" in some literature.
Integer. The number of components desired.
A vector of length(K) giving the tuning parameters.
Other parameters to be passed to arrayspc.
An object of class prcomp and converted_from_arrayspc,
which includes a list
element called $method, a character string describing the
pre-processing carried out and the type of PCA performed (used to annotate
plots). A check is carried out to see if the computation was successful
and a warning issued if it failed.
The scale choice autoscale scales the columns by their standard
deviation. Pareto scales by the square root of the standard
deviation.
H. Zou, T. Hastie and R. Tibshirani "Sparse Principal Components Analysis" J. Comp. Stat. Graphics vol. 15 no. 2 pgs. 265-286 (2006).
arrayspc for the underlying function,
c_pcaSpectra for classical PCA calculations,
r_pcaSpectra for robust PCA calculations,
irlba_pcaSpectra for PCA via the IRLBA algorithm.
Additional documentation at https://bryanhanson.github.io/ChemoSpec/
For displaying the results, ChemoSpecUtils::plotScree(), ChemoSpecUtils::plotScores(), plotLoadings(), plot2Loadings(), sPlotSpectra().
if (FALSE) {
# This example assumes the graphics output is set to ggplot2 (see ?GraphicsOptions).
library("ggplot2")
data(SrE.NMR)
pca <- s_pcaSpectra(SrE.NMR)
p1 <- plotScree(pca)
p1
p2 <- plotScores(SrE.NMR, pca, pcs = c(1, 2), ellipse = "cls", tol = 0.05)
p2 <- p2 + ggtitle("Scores: SrE NMR Data")
p2
p3 <- plotLoadings(SrE.NMR, pca, loads = 1:2, ref = 1)
p3 <- p3 + ggtitle("Loadings: SrE NMR Data")
p3
}