Wong-Zakai approximation for stochastic models of smoking

Abstract

In this study, Wong-Zakai approximation method has been used to obtain approximate solutions for two compartmental models of smoking dynamics. Stratonovich stochastic differential equation systems are obtained for these two stochastic models for the application of Wong-Zakai method. Wong-Zakai method is used together with the predictor-corrector deterministic approximation method where Adams-Bashforth method is used as the predictor pair and Adams-Moulton method is used as the corrector pair. Stochastic Runge-Kutta IV, Euler-Maruyama and stochastic Runge-Kutta strong order 1.0 schemes are also used to investigate the models and the results are compared to the results from Wong-Zakai approximation. The comparison shows that Wong-Zakai method is a reliable tool for the analysis of stochastic models and can be considered as an alternative investigation method for modeling studies. Solution graphs, error graphs and numerical results have been given as evidence to show that Wong-Zakai method can also be a reliable method for analyzing various models. An alternate technique for parallelizing the algorithm has also been given to decrease CPU times for Wong-Zakai method. This technique is suggested to overcome the extra calculation load that comes with Wong-Zakai method.