Open Access
February 2013 Functional data analysis in an operator-based mixed-model framework
Bo Markussen
Bernoulli 19(1): 1-17 (February 2013). DOI: 10.3150/11-BEJ389

Abstract

Functional data analysis in a mixed-effects model framework is done using operator calculus. In this approach the functional parameters are treated as serially correlated effects giving an alternative to the penalized likelihood approach, where the functional parameters are treated as fixed effects. Operator approximations for the necessary matrix computations are proposed, and semi-explicit and numerically stable formulae of linear computational complexity are derived for likelihood analysis. The operator approach renders the usage of a functional basis unnecessary and clarifies the role of the boundary conditions.

Citation

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Bo Markussen. "Functional data analysis in an operator-based mixed-model framework." Bernoulli 19 (1) 1 - 17, February 2013. https://doi.org/10.3150/11-BEJ389

Information

Published: February 2013
First available in Project Euclid: 18 January 2013

zbMATH: 1259.62001
MathSciNet: MR3019483
Digital Object Identifier: 10.3150/11-BEJ389

Keywords: determinant approximation , Gaussian process , Green’s function , operator approximation , random effect , serial correlation

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

Vol.19 • No. 1 • February 2013
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