baseline.als | R Documentation |
Baseline correction by 2nd derivative constrained weighted regression. Original algorithm proposed by Paul H. C. Eilers and Hans F.M. Boelens
baseline.als(spectra, lambda = 6, p = 0.05, maxit = 20)
spectra |
Matrix with spectra in rows |
lambda |
2nd derivative constraint |
p |
Weighting of positive residuals |
maxit |
Maximum number of iterations |
Iterative algorithm applying 2nd derivative constraints. Weights from previous
iteration is p
for positive residuals and 1-p
for negative residuals.
baseline |
Matrix of baselines corresponding to spectra |
corrected |
Matrix of baseline corrected spectra |
wgts |
Matrix of final regression weights |
Kristian Hovde Liland and Bjørn-Helge Mevik
Paul H. C. Eilers and Hans F.M. Boelens: Baseline Correction with Asymmetric Least Squares Smoothing
data(milk)
bc.als <- baseline(milk$spectra[1,, drop=FALSE], lambda=10, method='als')
## Not run:
plot(bc.als)
## End(Not run)
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