spec_pca {tidyspec} | R Documentation |
Perform Principal Component Analysis (PCA) on Spectral Data
Description
This function computes a Principal Component Analysis (PCA) on spectral data, excluding the wavenumber column from the analysis.
Usage
spec_pca(.data, wn_col = NULL, scale = TRUE, center = TRUE)
Arguments
.data |
A data frame containing spectral data, with one column representing wavenumbers and the remaining columns containing spectral intensity values. |
wn_col |
A string specifying the name of the column that contains the wavenumber values. If NULL, the function attempts to retrieve the default wavenumber column set by 'set_spec_wn()'. |
scale |
A logical value indicating whether the spectral data should be scaled (default is TRUE). |
center |
A logical value indicating whether the spectral data should be centered (default is TRUE). |
Value
A 'prcomp' object containing the PCA results, including principal components, standard deviations, and loadings.
Examples
set_spec_wn("Wavenumber")
pca_result <- spec_pca(CoHAspec)
summary(pca_result)
[Package tidyspec version 0.1.0 Index]