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Error Bounds for Dynamical Spectral Estimation.

ABSTRACT: 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.

SUBMITTER: Webber RJ

PROVIDER: S-EPMC8336423 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Error Bounds for Dynamical Spectral Estimation.

Webber Robert J RJ Thiede Erik H EH Dow Douglas D Dinner Aaron R AR Weare Jonathan J

SIAM journal on mathematics of data science 20210211 1

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 estimat ...[more]

PMID: 34355137

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