No Cover Image

Journal article 918 views 131 downloads

Estimation of intrinsic growth factors in a class of stochastic population model

Jingjie Li, Jiang-lun Wu Orcid Logo, Guang Zhang

Stochastic Analysis and Applications, Volume: 37, Issue: 4, Pages: 602 - 619

Swansea University Author: Jiang-lun Wu Orcid Logo

Check full text

DOI (Published version): 10.1080/07362994.2019.1605908

Abstract

This article discusses the problem of parameter estimation with nonlinear mean-reversion type stochastic differential equations (SDEs) driven by Brownian motion for population growth model. The estimator in the population model is the climate effects, population policy and environmental circumstance...

Full description

Published in: Stochastic Analysis and Applications
ISSN: 0736-2994 1532-9356
Published: Taylor & Francis 2019
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa49977
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: This article discusses the problem of parameter estimation with nonlinear mean-reversion type stochastic differential equations (SDEs) driven by Brownian motion for population growth model. The estimator in the population model is the climate effects, population policy and environmental circumstances which affect the intrinsic rate of growth r. The consistency and asymptotic distribution of the estimator θ is studied in our general setting. In the calculation method, unlike previous study, since the nonlinear feature of the model, it is difficult to obtain an explicit formula for the estimator. To solve this, some criteria are used to derive an asymptotically consistent estimator. Furthermore Girsanov transformation is used to simplify the equations, which then gives rise to the corresponding convergence of the estimator being with respect to a family of probability measures indexed by the dispersion parameter, while in the literature the existing results have dealt with convergence with respect to a given probability measure.
College: Faculty of Science and Engineering
Issue: 4
Start Page: 602
End Page: 619

Similar Items