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Error Bounds for Dynamical Spectral Estimation

Dynamical spectral estimation is a well-established numerical approach for estimating eigenvalues and eigenfunctions of the Markov transition operator from trajectory data. Although the approach has been widely applied in biomolecular simulations, its error properties remain poorly understood. Here...

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Detalles Bibliográficos
Autores principales: Webber, Robert J., Thiede, Erik H., Dow, Douglas, Dinner, Aaron R., Weare, Jonathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336423/
https://www.ncbi.nlm.nih.gov/pubmed/34355137
http://dx.doi.org/10.1137/20m1335984
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author Webber, Robert J.
Thiede, Erik H.
Dow, Douglas
Dinner, Aaron R.
Weare, Jonathan
author_facet Webber, Robert J.
Thiede, Erik H.
Dow, Douglas
Dinner, Aaron R.
Weare, Jonathan
author_sort Webber, Robert J.
collection PubMed
description Dynamical spectral estimation is a well-established numerical approach for estimating eigenvalues and eigenfunctions of the Markov transition operator from trajectory data. Although the approach has been widely applied in biomolecular simulations, its error properties remain poorly understood. Here we analyze the error of a dynamical spectral estimation method called “the variational approach to conformational dynamics” (VAC). We bound the approximation error and estimation error for VAC estimates. Our analysis establishes VAC’s convergence properties and suggests new strategies for tuning VAC to improve accuracy.
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spelling pubmed-83364232021-08-04 Error Bounds for Dynamical Spectral Estimation Webber, Robert J. Thiede, Erik H. Dow, Douglas Dinner, Aaron R. Weare, Jonathan SIAM J Math Data Sci Article Dynamical spectral estimation is a well-established numerical approach for estimating eigenvalues and eigenfunctions of the Markov transition operator from trajectory data. Although the approach has been widely applied in biomolecular simulations, its error properties remain poorly understood. Here we analyze the error of a dynamical spectral estimation method called “the variational approach to conformational dynamics” (VAC). We bound the approximation error and estimation error for VAC estimates. Our analysis establishes VAC’s convergence properties and suggests new strategies for tuning VAC to improve accuracy. 2021-02-11 2021 /pmc/articles/PMC8336423/ /pubmed/34355137 http://dx.doi.org/10.1137/20m1335984 Text en https://creativecommons.org/licenses/by/4.0/Published by SIAM under the terms of the Creative Commons 4.0 license
spellingShingle Article
Webber, Robert J.
Thiede, Erik H.
Dow, Douglas
Dinner, Aaron R.
Weare, Jonathan
Error Bounds for Dynamical Spectral Estimation
title Error Bounds for Dynamical Spectral Estimation
title_full Error Bounds for Dynamical Spectral Estimation
title_fullStr Error Bounds for Dynamical Spectral Estimation
title_full_unstemmed Error Bounds for Dynamical Spectral Estimation
title_short Error Bounds for Dynamical Spectral Estimation
title_sort error bounds for dynamical spectral estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336423/
https://www.ncbi.nlm.nih.gov/pubmed/34355137
http://dx.doi.org/10.1137/20m1335984
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