Stochastic Differential Equation Model to Prendiville Processes

被引:0
|
作者
Granita [1 ]
Bahar, Arifah [1 ,2 ]
机构
[1] Univ Teknol Malaysia, Dept Math Sci, Johor Baharu 81310, Malaysia
[2] UTM CIAM, Toulouse, France
关键词
Continuous Time Markov Chain; Forward Kolmogorov Equation; Stochastic Differential Equation; Prendiville processes; POPULATION-MODELS;
D O I
10.1063/1.4932498
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Prendiville process is another variation of the logistic model which assumes linearly decreasing population growth rate. It is a continuous time Markov chain (CTMC) taking integer values in the finite interval. The continuous time Markov chain can be approximated by stochastic differential equation (SDE). This paper discusses the stochastic differential equation of Prendiville process. The work started with the forward Kolmogorov equation in continuous time Markov chain of Prendiville process. Then it was formulated in the form of a central-difference approximation. The approximation was then used in Fokker-Planck equation in relation to the stochastic differential equation of the Prendiville process. The explicit solution of the Prendiville process was obtained from the stochastic differential equation. Therefore, the mean and variance function of the Prendiville process could be easily found from the explicit solution.
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页数:4
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