R: Robust Baseline Estimation

baseline.rfbaseline {baseline} | R Documentation

## 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)

[Package baseline version 1.2-1 Index]