cv_pcaSpectra: Cross-Validation of Classical PCA Results for a Spectra...

In ChemoSpec: Exploratory Chemometrics for Spectroscopy

Cross-Validation of Classical PCA Results for a Spectra Object

Description

This function carries out classical PCA on the data in a Spectra object using a cross-validation method. A simple re-write of Peter Filzmoser's pcaCV method with some small plotting changes.

Usage

cv_pcaSpectra(
  spectra,
  pcs,
  choice = "noscale",
  repl = 50,
  segments = 4,
  segment.type = c("random", "consecutive", "interleaved"),
  length.seg,
  trace = FALSE,
  ...
)

Arguments

spectra	An object of S3 class Spectra().
pcs	As per pcaCV where it is called amax; an integer giving the number of PC scores to include.
choice	A character string indicating the choice of scaling. One of c("noscale", "autoscale", "Pareto").
repl	As per pcaCV; the number of replicates to perform.
segments	As per pcaCV.
segment.type	As per pcaCV.
length.seg	As per pcaCV.
trace	As per pcaCV.
...	Parameters to be passed to the plotting routines.

Value

Invisibly, a list as described in pcaCV. Side effect is a plot.

Author(s)

Bryan A. Hanson, DePauw University. Derived from pcaCV.

References

K. Varmuza and P. Filzmoser Introduction to Multivariate Statistical Analysis in Chemometrics, CRC Press, 2009.

See Also

pcaCV for the underlying function. Additional documentation at https://bryanhanson.github.io/ChemoSpec/

Examples

# You need to install package "pls" for this example
if (requireNamespace("pls", quietly = TRUE)) {
  data(SrE.IR)
  pca <- cv_pcaSpectra(SrE.IR, pcs = 5)
}

ChemoSpec documentation built on April 15, 2025, 5:09 p.m.