tidyspec (version 0.1.0)

spec_pca: 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)

Value

A `prcomp` object containing the PCA results, including principal components, standard deviations, and loadings.

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).

Examples

# \donttest{
set_spec_wn("Wavenumber")
pca_result <- spec_pca(CoHAspec)
summary(pca_result)
# }