Abstract #300412

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JSM 2003 Abstract #300412
Activity Number: 357
Type: Topic Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract - #300412
Title: Smooth Coefficient Surfaces for Generalized Linear Regression
Author(s): Brian D. Marx*+ and Paul H. C. Eilers
Companies: Louisiana State University and Leiden University Medical Centre
Address: 149 Agric. Admin. Bldg., Baton Rouge, LA, 70803-0001,
Keywords: calibration transfer ; multivariate calibration ; signal regression ; tensor products ; varying coefficients ; p-splines
Abstract:

The Penalized Signal Regression (PSR) approach is broadened to more complex two-dimensional surfaces. Applications include chemometric spectra varying across temperature, used to predict a chemical component, or medical flourescence spectroscopic surfaces (emission and excitation), used to predict presence/absence of tumor features. Tensor product b-splines and difference penalties along the two dimensions, in the spirit of p-splines, are used to regularize estimation. In some applications a slice of the estimated coefficient surface is used to weigh an associtated spectrum, whereas in others the entire surface is used to produce an estimated linear predictor. We present the theory and apply multidimensional PSR to a published data set with good performance.

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