baseline.als {baseline}

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)