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Robust Smoothing: Smoothing Parameter Selection and Applications to Fluorescence Spectroscopy.

ABSTRACT: 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.

SUBMITTER: Lee JS

PROVIDER: S-EPMC2923818 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Robust Smoothing: Smoothing Parameter Selection and Applications to Fluorescence Spectroscopy.

Lee Jong Soo JS Cox Dennis D DD

Computational statistics & data analysis 20101201 12

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, an ...[more]

PMID: 20729976

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