Description Usage Arguments Value Author(s) See Also
penalized least squares algorithm for background fitting
1 | WhittakerSmooth(x,w,lambda)
|
x |
raman spectrum |
w |
binary masks (value of the mask is zero if a point belongs to peaks and one otherwise) |
lambda |
lambda is an adjustable parameter, it can be adjusted by user. The larger lambda is, the smoother z will be |
differences |
an integer indicating the order of the difference of penalties |
the fitted vector
Yizeng Liang ,Zhang Zhimin
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