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Robust smoothing: Smoothing parameter selection and applications to fluorescence spectroscopy

Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission spect...

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Bibliographic Details
Published in:Computational statistics & data analysis 2010-12, Vol.54 (12), p.3131-3143
Main Authors: Lee, Jong Soo, Cox, Dennis D.
Format: Article
Language:English
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Summary:Fluorescence spectroscopy has emerged in recent years as an effective way to detect cervical cancer. Investigation of the data preprocessing stage uncovered a need for a robust smoothing to extract the signal from the noise. Various robust smoothing methods for estimating fluorescence emission spectra are compared and data driven methods for the selection of smoothing parameter are suggested. The methods currently implemented in R for smoothing parameter selection proved to be unsatisfactory, and a computationally efficient procedure that approximates robust leave-one-out cross validation is presented.
ISSN:0167-9473
1872-7352
DOI:10.1016/j.csda.2009.08.001