SpectrumBackground: Background estimation.
In Peaks: Peaks

Description Usage Arguments Details Value Author(s) References

View source: R/zzz.R

This function calculates background spectrum from source spectrum and separates useful information (peaks) from useless information (background).

1 2	SpectrumBackground(y,iterations=100,decreasing=FALSE,order=c("2","4","6","8"), smoothing=FALSE,window=c("3","5","7","9","11","13","15"),compton=FALSE)

`y`	the vector of source spectrum
`iterations`	maximal width of clipping window
`decreasing`	direction of change of clipping window. If `TRUE` the window is decreasing, otherwise the window is increasing.
`order`	order of clipping filter
`smoothing`	logical variable whether the smoothing operation in the estimation of background will be included
`window`	width of smoothing window
`compton`	logical variable whether the estimation of Compton edge (step-like feature at the peaks positions) will be included

Method is based on Sensitive Nonlinear Iterative Peak (SNIP) clipping algorithm.

New value in the channel i is calculated (in the case of second-order clipping filter) with formula:

v_p(i)=min\{v_{p-1}(i),(v_{p-1}(i+p)+v_{p-1}(i-p))/2\}

Numeric vector with background profile.

Miroslav Morhác

C. G Ryan et al.: SNIP, a statistics-sensitive background treatment for the quantitative analysis of PIXE spectra in geoscience applications. NIM, B34 (1988), 396-402.

M. Morhác, J. Kliman, V. Matoucek, M. Veselský, I. Turzo.: Background elimination methods for multidimensional gamma-ray spectra. NIM, A401 (1997) 113-132.

D. D. Burgess, R. J. Tervo: Background estimation for gamma-ray spectroscopy. NIM 214 (1983), 431-434.

Peaks documentation built on May 29, 2017, 8:29 p.m.