Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/65638
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | On parameter estimation in population models II: multi-dimensional processes and transient dynamics |
Author: | Ross, J. Pagendam, D. Pollett, P. |
Citation: | Theoretical Population Biology, 2009; 75(2-3):123-132 |
Publisher: | Academic Press Inc |
Issue Date: | 2009 |
ISSN: | 0040-5809 1096-0325 |
Statement of Responsibility: | J. V. Ross, D. E. Pagendam and P. K. Pollett |
Abstract: | Recently, a computationally-efficient method was presented for calibrating a wide-class of Markov processes from discrete-sampled abundance data. The method was illustrated with respect to one-dimensional processes and required the assumption of stationarity. Here we demonstrate that the approach may be directly extended to multi-dimensional processes, and two analogous computationally-efficient methods for non-stationary processes are developed. These methods are illustrated with respect to disease and population models, including application to infectious count data from an outbreak of "Russian influenza" (A/USSR/1977 H1N1) in an educational institution. The methodology is also shown to provide an efficient, simple and yet rigorous approach to calibrating disease processes with gamma-distributed infectious period. |
Keywords: | Ecology epidemiology parameter estimation infectious period distribution Markov processes dynamic landscape stochasticity diffusion approximations |
Rights: | © 2009 Elsevier Inc. All rights reserved. |
DOI: | 10.1016/j.tpb.2008.12.002 |
Published version: | http://dx.doi.org/10.1016/j.tpb.2008.12.002 |
Appears in Collections: | Aurora harvest 5 Mathematical Sciences publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.