371 citations · 642 across the 29 of their papers we have counts for
8 papers · 1 filter
Variance of finite difference methods for reaction networks with non-Lipschitz rate functions
David F. Anderson, Chaojie Yuan
Parametric sensitivity analysis is a critical component in the study of mathematical models of physical systems. Due to its simplicity, finite difference methods are used extensive…
Conditional Monte Carlo for Reaction Networks
David F. Anderson, Kurt W. Ehlert
Reaction networks are often used to model interacting species in fields such as biochemistry and ecology. When the counts of the species are sufficiently large, the dynamics of the…
Low variance couplings for stochastic models of intracellular processes with time-dependent rate functions
David F. Anderson, Chaojie Yuan
A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and…
Computational complexity analysis for Monte Carlo approximations of classically scaled population processes
David F. Anderson, Desmond J. Higham, Yu Sun
We analyze and compare the computational complexity of different simulation strategies for Monte Carlo in the setting of classically scaled population processes. This allows a rang…
Hybrid Pathwise Sensitivity Methods for Discrete Stochastic Models of Chemical Reaction Systems
Elizabeth Skubak Wolf, David F. Anderson
Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Para…
An asymptotic relationship between coupling methods for stochastically modeled population processes
David F. Anderson, Masanori Koyama
This paper is concerned with elucidating a relationship between two common coupling methods for the continuous time Markov chain models utilized in the cell biology literature. The…