ChemoSpec: aovPCAscores – R documentation

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aovPCAscores

Plot ANOVA-PCA Scores from a Spectra Object

Description

Uses the results from aov_pcaSpectra to conduct PCA and plot the scores. Argument plot is used to select a matrix from those in LM. The residual error matrix is then added to the selected matrix before performing PCA. Use names(LM) to see which factor is stored in which matrix.

Usage

aovPCAscores(spectra, LM, plot = 1, type = "class", choice = NULL, ...)

Arguments

`spectra`	An object of S3 class `Spectra`.
`LM`	List of matrices created by `aov_pcaSpectra`.
`plot`	An integer specifying which scores to plot.
`type`	Either classical ("cls") or robust ("rob"); Results in either `c_pcaSpectra` or `r_pcaSpectra` being called on the `Spectra` object.
`choice`	The type of scaling to be performed. See `c_pcaSpectra` and `r_pcaSpectra` for details.
`...`	Additional parameters to be passed to `plotScores`. For example, you can plot confidence ellipses this way. Note that ellipses are drawn based on the groups in `spectra$groups`, but the separation done by `aov_pcaSpectra` is based on argument `fac`. These may not correspond, but you can edit `spectra$groups` to match if necessary.

Value

Returns the PCA results, and creates the requested plot.

Author(s)

Matthew J. Keinsley and Bryan A. Hanson, DePauw University.

References

Pinto, Bosc, Nocairi, Barros, and Rutledge. "Using ANOVA-PCA for Discriminant Analysis: ..." Analytica Chimica Acta 629.1-2 (2008): 47-55.

Harrington, Vieira, Espinoza, Nien, Romero, and Yergey. "Analysis of Variance–Principal Component Analysis: ..." Analytica Chimica Acta 544.1-2 (2005): 118-27.