airPLS: Baseline correction using adaptive iteratively reweighted...

In zmzhang/airPLS_R: adaptive iteratively reweighted Penalized Least Squares for baseline correction

Baseline correction using adaptive iteratively reweighted penalized least squares

Description

Baseline drift always blurs or even swamps signals and deteriorates analytical results, particularly in multivariate analysis. It is necessary to correct baseline drift to perform further data analysis. Simple or modified polynomial fitting has been found to be effective in some extent. However, this method requires user intervention and prone to variability especially in low signal-to-noise ratio environments. The proposed adaptive iteratively reweighted Penalized Least Squares (airPLS) algorithm doesn't require any user intervention and prior information, such as detected peaks. It iteratively changes weights of sum squares errors (SSE) between the fitted baseline and original signals, and the weights of SSE are obtained adaptively using between previously fitted baseline and original signals. This baseline estimator is general, fast and flexible in fitting baseline.

Details

Package:	airPLS
Type:	Package
Version:	1.0.0
Date:	2009-10-09
License:	GPL (>= 2)

Author(s)

yizeng liang<[e-mail]>, zhimin zhang <[e-mail]>, chen shan <[e-mail]>

zmzhang/airPLS_R documentation built on Aug. 5, 2023, 8:24 a.m.