@article {IOPORT.05615595,
    author       = {Sandmann, Werner},
    title        = {Sequential estimation for prescribed statistical accuracy in stochastic simulation of biological systems.},
    year         = {2009},
    journal      = {Mathematical Biosciences},
    volume       = {221},
    number       = {1},
    issn         = {0025-5564},
    pages        = {43-53},
    publisher    = {Elsevier Science Inc., New York, NY},
    doi          = {10.1016/j.mbs.2009.06.006},
    abstract     = {Summary: 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.},
    identifier   = {05615595},
}