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Kernelize transforms bilinear data (exponential decays) using kernels to provide trilinear data.
It implements all-at-once model for coupled matrix and tensor analysis (CMTF and ACMTF), enabling joint analysis of matrices + higher‐order tensors.
MSC algorithm for correcting multiplicative and additive scatter effects in spectral data.
NIPALS performs PCA on data using iterative least squares and deflation steps. It can deal with missing values.
A Whittaker smoother using penalized LS & iterative imputation to smooth data & fill gaps.
The PARAFAC-ALS (Lite version) algorithm unmixes trilinear data to obtain the pure components.
Applies the Whittaker smoother using penalized least squares to reduce noise.
MATLAB codes to access Renishaw WiRE .wdf Raman data files, with read/write access to spectra, mapped data, and header metadata.
This function allows to quickly simulate n- gaussian spectra.
Creates a combined PCA plot with scores, loadings, and violin plots to visualize sample groups, variable impact, and distributions.