title: Sequential estimation for prescribed statistical accuracy in stochastic simulation of biological systems.
abstract: Stochastic simulation of biological systems proceeds by repeatedly generating sample paths or trajectories of the underlying stochastic process, from which many relevant and important system properties can be obtained. While a great deal of research is targeted towards accelerated trajectory generation, issues concerned with the variability across trajectories are often neglected. Advanced methods for properly quantifying the statistical accuracy and determining a reasonable number of trajectories are hardly addressed formally in the context of biological system simulation, though mathematical statistics provides a large body of powerful theory. We invoke this theory and show how mathematically well-founded sequential estimation approaches serve for systematically generating enough but not too many trajectories for achieving a certain prescribed accuracy. The practical applicability is demonstrated and illustrated by numerical examples through simulation studies of an immigration-death process and a gene regulatory network.
authors: Clausthal University of Technology, Department of Mathematics, Clausthal-Zellerfeld, Germany. werner.sandmann@tu-clausthal.de
authors: Werner
authors: W
authors: Sandmann
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016001:Confidence Intervals; D004812:Epidemiologic Methods; D053263:Gene Regulatory Networks; D008390:Markov Chains; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D011157:Population Dynamics; D013269:Stochastic Processes