A Markov Embedding Approximation for a Stochastic Population Model with Exogenous Disturbances

Bruce Ayati; Claudia Neuhauser

doi:10.1023/A:1012212725398

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A Markov Embedding Approximation for a Stochastic Population Model with Exogenous Disturbances

Journal article

Peer reviewed

A Markov Embedding Approximation for a Stochastic Population Model with Exogenous Disturbances

Bruce Ayati and Claudia Neuhauser

Methodology And Computing In Applied Probability, Vol.3(2), pp.123-133

06/2001

DOI: 10.1023/A:1012212725398

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Abstract

We present and study an approximation scheme for the mean of a stochastic simulation that models a population subject to nonlinear birth and exogenous disturbances. We use the information from the probability distribution for the disturbance times to construct a method that improves upon the mean-field approximation. We show through two example systems the effectiveness of the Markov embedding approximation and discuss the contexts in which it is an appropriate method.

Economics general

Life Sciences, general

Statistics, general

Business/Management Science, general

Statistics

exogenous disturbance

Markov embedding

Electronic and Computer Engineering

mean-field

Details

Title: Subtitle: A Markov Embedding Approximation for a Stochastic Population Model with Exogenous Disturbances
Creators: Bruce Ayati - Institute for Mathematics and its Applications University of Minnesota Minneapolis MN 55455
Claudia Neuhauser - School of Mathematics and Department of Ecology, Evolution and Behavior University of Minnesota Minneapolis MN 55455
Resource Type: Journal article
Publication Details: Methodology And Computing In Applied Probability, Vol.3(2), pp.123-133
Publisher: Kluwer Academic Publishers; Boston
DOI: 10.1023/A:1012212725398
ISSN: 1387-5841
eISSN: 1573-7713
Language: English
Date published: 06/2001
Academic Unit: Mathematics; Orthopedics and Rehabilitation
Record Identifier: 9983986094302771

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