JSM 2005 - Toronto

Abstract #304419

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Activity Number: 437
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #304419
Title: Penalized Likelihood Estimation of a Mixed-effect Transfer Function Model
Author(s): Elizabeth Hansen*+ and Kung-Sik Chan
Companies: The University of Iowa and The University of Iowa
Address: 913 Dewey St, Iowa City, IA, 52245, United States
Keywords: cross-validation ; smoothing ; multivariate time series ; iterative regression ; EM algorithm
Abstract:

We consider the problem of estimating a mixed-effect transfer function model with a panel of contemporaneously correlated times series data. To alleviate the problems of multicollinearity and model complexity, the mean function is assumed to be smooth. The smoothness of the function is measured by the square norm of the second differences. The model can be estimated by the penalized likelihood method. We develop an iterative procedure via the EM algorithm for maximizing the penalized likelihood. A cod-spawning example that motivated this approach also is presented.

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