Local Asymmetric Least Squares (LAsLS) applies localized Whittaker and asymmetry parameters for baseline correction in spectral data. It uses an iteratively reweighted least squares approach to adapt to varying background trends. The LAsLS method effectively handles complex baselines by permitting distinct asymmetry and smoothing penalties on user-defined intervals, enhancing the accuracy of subsequent spectral analyses.
Eilers, P. H. C.; Boelens, H. F. M. (2005). Baseline correction with asymmetric least squares smoothing. Leiden University Medical Centre Report, 1(1), 5.
Gomez-Sanchez, A. Local Asymmetric Least Squares (LAsLS). Lovelace's Square / GitHub repository. https://github.com/LovelaceSquare/lasls-cl Version 1.1.