baseline: baseline.rfbaseline – R documentation

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baseline.rfbaseline

Robust Baseline Estimation

Description

Wrapper for Andreas F. Ruckstuhl, Matthew P. Jacobson, Robert W. Field, James A. Dodd's algorithm based on LOWESS and weighted regression

Usage

baseline.rfbaseline(spectra, span = 2/3, NoXP = NULL, maxit = c(2, 2),
  b = 3.5, weight = NULL, Scale = function(r) median(abs(r))/0.6745,
  delta = NULL, SORT = FALSE, DOT = FALSE, init = NULL)

Arguments

`spectra`	Matrix with spectra in rows
`span`	Amount of smoothing (by fraction of points)
`NoXP`	Amount of smoothing (by number of points)
`maxit`	Maximum number of iterations in robust fit
`b`	Tuning constant in the biweight function
`weight`	Optional weights to be given to individual observations
`Scale`	S function specifying how to calculate the scale of the residuals
`delta`	Nonnegative parameter which may be used to save computation. (See `rfbaseline`
`SORT`	Boolean variable indicating whether x data must be sorted.
`DOT`	Disregard outliers totally (boolean)
`init`	Values of initial fit

Details

Most of the code is the original code as given by the authors. The ability to sort by X-values has been removed and ability to handle multiple spectra has been added

Value

`baseline`	Matrix of baselines corresponding to spectra `spectra`
`corrected`	Matrix of baseline corrected spectra

Author(s)

Kristian Hovde Liland and Bjørn-Helge Mevik

References

Andreas F. Ruckstuhl, Matthew P. Jacobson, Robert W. Field, James A. Dodd: Baseline subtraction using robust local regression estimation

Examples

data(milk)
bc.rbe <- baseline(milk$spectra[1,, drop=FALSE], method='rfbaseline',
  span=NULL, NoXP=1000)
## Not run: 
	plot(bc.rbe)

## End(Not run)

baseline

Baseline Correction of Spectra

v1.3-1

GPL-2

Authors

Kristian Hovde Liland [aut, cre], Bjørn-Helge Mevik [aut], Roberto Canteri [ctb]

Initial release

2020-09-10