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Abstract Details

Activity Number: 356
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #306109
Title: Peak Locating for Functional Data
Author(s): Lu wang*+ and Dennis Dean Cox
Companies: and Rice University
Address: 1515 Bissonnet Unit 170, Houston, TX, 77005, United States
Keywords: peak location ; non-linear random effect model
Abstract:

Cervical cancer is easy to prevent if detected early. We are investigating the use of spectroscopic devices that have been shown to have power to detect cancerous and pre-cancerous lesions. One of them major problems with bio- medical applications of optical spectroscopy has been repeatability of the measurements. Rhodamine is one of the mostly commonly used standards in fluorescence spectroscopy. The measured spectra are functional data with variations due to different devices, measurement conditions, excitation wavelengths and some operational effects. The observed curve peak locations may be shifted by contamination fluorescence. To estimate the true spectral peak locations, we propose a model that incorporates the proportion of light from the eal spectrum, together with the effect of contaminations. Simulation and real data application show that the proposed model provides accurate estimation of intensity peak locations and heights.


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