baseline.als: Asymmetric Least Squares

In khliland/baseline: Baseline Correction of Spectra

Asymmetric Least Squares

Description

Baseline correction by 2nd derivative constrained weighted regression. Original algorithm proposed by Paul H. C. Eilers and Hans F.M. Boelens

Usage

baseline.als(spectra, lambda = 6, p = 0.05, maxit = 20)

Arguments

spectra	Matrix with spectra in rows
lambda	2nd derivative constraint
p	Weighting of positive residuals
maxit	Maximum number of iterations

Details

Iterative algorithm applying 2nd derivative constraints. Weights from previous iteration is p for positive residuals and 1-p for negative residuals.

Value

baseline	Matrix of baselines corresponding to spectra spectra
corrected	Matrix of baseline corrected spectra
wgts	Matrix of final regression weights

Author(s)

Kristian Hovde Liland and Bjørn-Helge Mevik

References

Paul H. C. Eilers and Hans F.M. Boelens: Baseline Correction with Asymmetric Least Squares Smoothing

Examples

data(milk)
bc.als <- baseline(milk$spectra[1,, drop=FALSE], lambda=10, method='als')
## Not run: 
plot(bc.als)

## End(Not run)

khliland/baseline documentation built on Nov. 24, 2023, 9:28 a.m.