Model Discrimination in Copolymerization Using the Sequential Bayesian Monte Carlo Method

• Published in: Macromolecular theory and simulations Vol. 25; no. 5; pp. 435 - 448
• Main Authors: Masoumi, Samira, Duever, Thomas A.
• Format: Journal Article
• Language: English
• Published: Weinheim Blackwell Publishing Ltd 01.09.2016; Wiley Subscription Services, Inc
• Subjects: Bayesian analysis; Computer simulation; Copolymerization; Copolymers; design of experiments; Discrimination; Markov analysis; Mathematical models; Methods; modeling copolymerization; Monte Carlo methods; Monte Carlo simulation; penultimate; sequential Bayesian adaptive Metropolis Hasting model discrimination; terminal; Terminals
• ISSN: 1022-1344; 1521-3919
• DOI: 10.1002/mats.201600009

The authors have introduced and extended the sequential Bayesian Monte Carlo model discrimination (SBMCMD) method described in previous studies by Masoumi et al. for the purpose of discriminating between mechanistic models via designed experiments. The features of the Markov Chain Monte Carlo methods utilized in SBMCMD allow this method to work with a wide range of nonlinear models. Here, SBMCMD has been applied to simulated copolymerization systems to compare its performance with other statistical discrimination methods used in previous studies by Burke et al. In addition, the Hsiang and Reilly method has been reapplied to the same copolymerization systems to address questions arising from previous work on this subject. The results of applying the SBMCMD method show that it is possible to choose the best model correctly with fewer experiments compared to the previously studied methods. Results also confirm that copolymer composition data do not provide enough information to discriminate between terminal and penultimate data. A sequential Bayesian and Monte Carlo based procedure is utilized to discriminate between simulated copolymerization systems. Performance of this approach is compared with that of other statistical discrimination methods and the benefits of the utilized method are discussed.