Repository: Freie Universität Berlin, Math Department

Estimation and uncertainty of reversible Markov models

Trendelkamp-Schroer, B. and Wu, H. and Paul, F. and Noé, F. (2015) Estimation and uncertainty of reversible Markov models. J. Chem. Phys., 143 (17). p. 174101.

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Official URL: http://dx.doi.org/10.1063/1.4934536

Abstract

Reversibility is a key concept in Markov models and Master-equation models of molecular kinetics. The analysis and interpretation of the transition matrix encoding the kinetic properties of the model relies heavily on the reversibility property. The estimation of a reversible transition matrix from simulation data is therefore crucial to the successful application of the previously developed theory. In this work we discuss methods for the maximum likelihood estimation of transition matrices from finite simulation data and present a new algorithm for the estimation if reversibility with respect to a given stationary vector is desired. We also develop new methods for the Bayesian posterior inference of reversible transition matrices with and without given stationary vector taking into account the need for a suitable prior distribution preserving the meta- stable features of the observed process during posterior inference. All algorithms here are implemented in the PyEMMA software - this http URL - as of version 2.0.

Item Type:Article
Subjects:Physical Sciences
Mathematical and Computer Sciences
Divisions:Department of Mathematics and Computer Science > Institute of Mathematics > Comp. Molecular Biology
ID Code:1700
Deposited By: BioComp Admin
Deposited On:19 Jul 2015 21:41
Last Modified:28 Jun 2017 09:40

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