skip to main content

SciTech ConnectSciTech Connect

Title: Stochastic differential equation model to Prendiville processes

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.
Authors:
 [1] ;  [1] ;  [2]
  1. Dept. of Mathematical Science, Universiti Teknologi Malaysia, 81310, Johor Malaysia (Malaysia)
  2. (UTM-CIAM) (Malaysia)
Publication Date:
OSTI Identifier:
22492505
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1682; Journal Issue: 1; Conference: SKSM22: 22. National symposium on mathematical sciences - Strengthening research and collaboration of mathematical sciences in Malaysia, Selangor (Malaysia), 24-26 Nov 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; APPROXIMATIONS; CHAPMAN-KOLMOGOROV EQUATION; FOKKER-PLANCK EQUATION; MARKOV PROCESS; MATHEMATICAL SOLUTIONS; VARIATIONS