Bayesian Parameters Estimation for the Stochastic Differential Delay Equation: A Simulation Study
DOI:
https://doi.org/10.36322/jksc.176(A).19366Keywords:
stochastic differential delay equations, geometric Brownian motion, Bayesian estimationAbstract
This paper dealt with the estimation of the parameters of stochastic differential delay equations through simulated experiments and compared their results with the traditional model called the geometric Brownian motion. The use of numerical methods in finding the numerical solution to the stochastic differential delay equations is done without addressing the estimation of the coefficient of these equations. As estimating the parameters of this type of equations is necessary to understand the behavior of the studied phenomenon, especially since there are phenomena with random behavior that depend on historical data (delay parameter). It is also known that there are difficulties in estimating the delay parameters of stochastic differential equations, which confront many interested researchers. So the stochastic differential delay equations parameters were estimated using Bayesian method. The results of the simulation experiments showed the superiority of the stochastic differential delay equation model over the geometric Brownian motion model.
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