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Stochastic Population Processes – Analysis, Approximations, Simulations - Oxford Scholarship Online
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Stochastic Population Processes: Analysis, Approximations, Simulations

Eric Renshaw


The vast majority of random processes in the real world have no memory — the next step in their development depends purely on their current state. Stochastic realizations are therefore defined purely in terms of successive event-time pairs, and such systems are easy to simulate irrespective of their degree of complexity. However, whilst the associated probability equations are straightforward to write down, their solution usually requires the use of approximation and perturbation procedures. Traditional books, heavy in mathematical theory, often ignore such methods and attempt to force problem ... More

Keywords: random processes, stochastic realizations, even-time pairs, probability equations, approximation

Bibliographic Information

Print publication date: 2011 Print ISBN-13: 9780199575312
Published to Oxford Scholarship Online: September 2011 DOI:10.1093/acprof:oso/9780199575312.001.0001


Affiliations are at time of print publication.

Eric Renshaw, author
Emeritus Professor of Statistics, University of Strathclyde, UK
Author Webpage