Meerbach, E. and Latorre, J.C. and Schütte, Ch. (2012) Sequential Change Point Detection in Molecular Dynamics Trajectories. Multicale Model. Sim., 10 (4). pp. 12631291.

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Official URL: http://dx.doi.org/10.1137/110850621
Abstract
Motivated from a molecular dynamics context we propose a sequential change point detection algorithm for vectorvalued autoregressive models based on Bayesian model selection. The algorithm does not rely on any sampling procedure or assumptions underlying the dynamics of the transitions and is designed to cope with highdimensional data. We show the applicability of the algorithm on a time series obtained from numerical simulation of a pentapeptide molecule.
Item Type:  Article 

Subjects:  Mathematical and Computer Sciences > Mathematics > Applied Mathematics 
Divisions:  Department of Mathematics and Computer Science > Institute of Mathematics > Cellular Mechanics Group Department of Mathematics and Computer Science > Institute of Mathematics > BioComputing Group 
ID Code:  1123 
Deposited By:  BioComp Admin 
Deposited On:  06 Feb 2012 14:42 
Last Modified:  03 Mar 2017 14:41 
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