Implementation of variable parameters in the Krylov-based finite state projection for solving the chemical master equation

H.D. Vo and R.B. Sidje

Applied Mathematics and Computation, 2017, vol. 293, issue C, 334-344

Abstract: The finite state projection (FSP) algorithm is a reduction method for solving the chemical master equation (CME). The Krylov-FSP improved on the original FSP by using an embedded scheme where the action of the matrix exponential is evaluated by the Krylov subspace method of Expokit for greater efficiency. There are parameters that impact the method, such as the stepsize that must be controlled to ensure the accuracy of the computed matrix exponentials, or to ensure the accuracy of the FSP. Other parameters include the dimension of the Krylov basis, or even the extent of reachability when expanding the FSP. In this work, we incorporate adaptive strategies to automatically vary these parameters. Numerical experiments comparing the resulting variants are reported, showing how certain choices perform better than others.

Keywords: Matrix exponential; Adaptive Krylov method; Chemical master equation; Finite state projection (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300316305082
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:293:y:2017:i:c:p:334-344

DOI: 10.1016/j.amc.2016.08.013

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().