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Research in the Mathematical Sciences

, 4:14

Frontiers in Applied and Computational Mathematics: Special Collection in Honor of Bjorn Engquist in the Occasion of His 70th Birthday

Abstract

This paper describes versions of OPAL, the Occam-Plausibility Algorithm Farrell et al. in J Comput Phys 295:189–208, 2015 in which the use of Bayesian model plausibilities is replaced with information-theoretic methods, such as the Akaike information criterion and the Bayesian information criterion. Applications to complex systems of coarse-grained molecular models approximating atomistic models of polyethylene materials are described. All of these model selection methods take into account uncertainties in the model, the observational data, the model parameters, and the predicted quantities of interest. A comparison of the models chosen by Bayesian model selection criteria and those chosen by the information-theoretic criteria is given.

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Author: Kathryn Farrell-Maupin - J. T. Oden

Source: https://link.springer.com/



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