Numerical methods for a stochastic generalized logistic model

Abstract

In this project, we study the logistic model which has been developed in the form of a stochastic differential equation model. We will compare the performance of six numerical methods, namely Euler-Maruyama, two point simplified weak Euler, three-point simplified weak Euler, simplified order 2.0 weak Taylor, explicit order 2.0 weak and order 2.0 weak predictor-corrector with the generalized logistic stochastic differential equation model in terms of the weak order of convergence and the run time.