Stochastic Population Processes: Analysis, Approximations, Simulations

Paperback | April 19, 2015

byEric Renshaw

not yet rated|write a review
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 oftheir degree of complexity. However, whilst the associated probability equations are straightforward to write down, their solution usually requires the use of approximation and perturbation.

Pricing and Purchase Info

$73.50

Ships within 1-3 weeks
Ships free on orders over $25

From the Publisher

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 oftheir degree of complexity. However, whilst...

Eric Renshaw graduated from Imperial College, London with a B.Sc. in Mathematics, studied for the Diploma in Statistics at Manchester University, and then researched for his M.Phil. and Ph.D. degrees in spatial stochastic population processes at Sussex and Edinburgh Universities. He joined the staff of Edinburgh University in 1969, fi...

other books by Eric Renshaw

Forgotten Sioux Falls
Forgotten Sioux Falls

Paperback|Oct 15 2012

$22.24 online$24.99list price(save 11%)
Format:PaperbackDimensions:672 pages, 9.69 × 6.73 × 0.68 inPublished:April 19, 2015Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198739060

ISBN - 13:9780198739067

Customer Reviews of Stochastic Population Processes: Analysis, Approximations, Simulations

Reviews

Extra Content

Table of Contents

Preface1. Introduction2. Simple Markov Population Processes3. General Markov Population Processes4. The Random Walk5. Markov Chains6. Markov Processes in Continuous Time and Space7. Modelling Bivariate Processes8. Two-Species Interaction Processes9. Spatial Processes10. Spatial-Temporal ExtensionsReferencesIndex