keywords: Stochastic differential equation, rice production, wiener process, prediction
The study assessed the Stochastic Differential Equation (SDE) model of the variation in rice production in Benue State, Nigeria. We considered variation in rice output to be subject to random influence driven by the Wiener process which is a derivative of Brownian motion. The study used secondary data from Benue State Agricultural and Rural Development Authority (BENARDA) for the period of 23 years (1986-2009). The data was analyzed using descriptive statistics to determine the drift and the volatility coefficients which constitutes the basic parameter of an SDE. The resulting model was solved numerically using the Stochastic Runge-Kutta Scheme. Result obtained from our model shows the trend in Rice production and a 5th degree interpolating polynomial was passed through the trajectory of the plot of the simulated data so as to make predictions. The results generated from the simulation were subjected to test for significance using the student T-test for independent data set and was found not to have significant difference. Result of our model agrees with the work of Henri (2007) and Rajoti (2014). However in our work we used parameters from the study area rather than the assumed values used in other work. We conclude that the model is suitable for prediction of rice output.