Error Bounds for Dynamical Spectral Estimation.

Autor:	Webber RJ; Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 USA., Thiede EH; Department of Chemistry, University of Chicago, Chicago, IL 60637 USA., Dow D; Department of Mathematics, University of Chicago, Chicago, IL 60637 USA., Dinner AR; Department of Chemistry, University of Chicago, Chicago, IL 60637 USA., Weare J; Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 USA.
Jazyk:	angličtina
Zdroj:	SIAM journal on mathematics of data science [SIAM J Math Data Sci] 2021; Vol. 3 (1), pp. 225-252. Date of Electronic Publication: 2021 Feb 11.
DOI:	10.1137/20m1335984
Abstrakt:	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.
Databáze:	MEDLINE
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