scholarly journals The subtle business of model reduction for stochastic chemical kinetics

2009 ◽  
Vol 130 (6) ◽  
pp. 064103 ◽  
Author(s):  
Dan T. Gillespie ◽  
Yang Cao ◽  
Kevin R. Sanft ◽  
Linda R. Petzold
2008 ◽  
Vol 129 (24) ◽  
pp. 244112 ◽  
Author(s):  
Carlos A. Gómez-Uribe ◽  
George C. Verghese ◽  
Abraham R. Tzafriri

2015 ◽  
Vol 5 (3) ◽  
pp. 420-452 ◽  
Author(s):  
Tae-Hyuk Ahn ◽  
◽  
Xiaoying Han ◽  
Adrian Sandu ◽  
◽  
...  

2013 ◽  
Vol 58 (3) ◽  
pp. 592-626 ◽  
Author(s):  
Alen Alexanderian ◽  
Francesco Rizzi ◽  
Muruhan Rathinam ◽  
Olivier P. Le Maître ◽  
Omar M. Knio

2005 ◽  
Vol 123 (16) ◽  
pp. 164115 ◽  
Author(s):  
Eric L. Haseltine ◽  
James B. Rawlings

2007 ◽  
Vol 126 (3) ◽  
pp. 034302 ◽  
Author(s):  
Dan T. Gillespie ◽  
Sotiria Lampoudi ◽  
Linda R. Petzold

2011 ◽  
Vol 43 (4) ◽  
pp. 1005-1026 ◽  
Author(s):  
Tuğrul Dayar ◽  
Werner Sandmann ◽  
David Spieler ◽  
Verena Wolf

Systems of stochastic chemical kinetics are modeled as infinite level-dependent quasi-birth-and-death (LDQBD) processes. For these systems, in contrast to many other applications, levels have an increasing number of states as the level number increases and the probability mass may reside arbitrarily far away from lower levels. Ideas from Lyapunov theory are combined with existing matrix-analytic formulations to obtain accurate approximations to the stationary probability distribution when the infinite LDQBD process is ergodic. Results of numerical experiments on a set of problems are provided.


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