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The Annals of Applied Probability 2011, Vol. 21, No. 6, 22262262
 

Summary: The Annals of Applied Probability
2011, Vol. 21, No. 6, 22262262
DOI: 10.1214/10-AAP756
Institute of Mathematical Statistics, 2011
ERROR ANALYSIS OF TAU-LEAP SIMULATION METHODS
BY DAVID F. ANDERSON1, ARNAB GANGULY2 AND THOMAS G. KURTZ2
University of Wisconsin, Madison
We perform an error analysis for numerical approximation methods of
continuous time Markov chain models commonly found in the chemistry and
biochemistry literature. The motivation for the analysis is to be able to com-
pare the accuracy of different approximation methods and, specifically, Euler
tau-leaping and midpoint tau-leaping. We perform our analysis under a scal-
ing in which the size of the time discretization is inversely proportional to
some (bounded) power of the norm of the state of the system. We argue that
this is a more appropriate scaling than that found in previous error analyses in
which the size of the time discretization goes to zero independent of the rest
of the model. Under the present scaling, we show that midpoint tau-leaping
achieves a higher order of accuracy, in both a weak and a strong sense, than
Euler tau-leaping; a result that is in contrast to previous analyses. We present
examples that demonstrate our findings.

  

Source: Anderson, David F. - Department of Mathematics, University of Wisconsin at Madison
Kurtz, Tom - Departments of Mathematics & Statistics, University of Wisconsin at Madison

 

Collections: Mathematics