ChemoSpec: cv_pcaSpectra – R documentation

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cv_pcaSpectra

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.

Examples

data(SrE.IR)
pca <- cv_pcaSpectra(SrE.IR, pcs = 5)

ChemoSpec

Exploratory Chemometrics for Spectroscopy

v5.3.11

GPL-3

Authors

Bryan A. Hanson [aut, cre] (<https://orcid.org/0000-0003-3536-8246>), Mike Bostock [cph, ctb] (author of the d3.js library used by plotSpectraJS, http://d3js.org), Matt Keinsley [ctb] (author of initial AOV-PCA code)

Initial release

2021-03-24