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On the emergence of random initial conditions in fluid limits


Barbour, A D; Chigansky, Pavel; Klebaner, Fima C (2016). On the emergence of random initial conditions in fluid limits. Journal of Applied Probability, 53(4):1193-1205.

Abstract

The paper presents a phenomenon occurring in population processes that start near zero and have large carrying capacity. By the classical result of Kurtz (1970), such processes, normalized by the carrying capacity, converge on finite intervals to the solutions of ordinary differential equations, also known as the fluid limit. When the initial population is small relative to carrying capacity, this limit is trivial. Here we show that, viewed at suitably chosen times increasing to infinity, the process converges to the fluid limit, governed by the same dynamics, but with a random initial condition. This random initial condition is related to the martingale limit of an associated linear birth and death process.

Abstract

The paper presents a phenomenon occurring in population processes that start near zero and have large carrying capacity. By the classical result of Kurtz (1970), such processes, normalized by the carrying capacity, converge on finite intervals to the solutions of ordinary differential equations, also known as the fluid limit. When the initial population is small relative to carrying capacity, this limit is trivial. Here we show that, viewed at suitably chosen times increasing to infinity, the process converges to the fluid limit, governed by the same dynamics, but with a random initial condition. This random initial condition is related to the martingale limit of an associated linear birth and death process.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Physical Sciences > General Mathematics
Social Sciences & Humanities > Statistics, Probability and Uncertainty
Language:English
Date:2016
Deposited On:27 Dec 2017 15:06
Last Modified:26 Jan 2022 14:36
Publisher:Applied Probability Trust
ISSN:0021-9002
Funders:Australian Research Council
OA Status:Green
Publisher DOI:https://doi.org/10.1017/jpr.2016.74
  • Content: Accepted Version
  • Language: English