Design and Development of Stochastic Modelling for Solanum Tuberosum Production in India

Abstract

This study aims at design and development of stochastic modelling for Solanum tuberosum production in India based on S. tuberosum production during the years from 1950 to 2018. The study considers Autoregressive (AR), Moving Average (MA) and ARIMA processes to select the appropriate ARIMA model for S. tuberosum production in India. Based on ARIMA (p,d,q) and its components Autocorrelation Function (ACF), Partial Autocorrelation Function(PACF), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Normalized BIC and Box-Ljung Q statistics estimated, ARIMA (1,1,0) was selected. Based on the chosen model, it could be predicted that S. tuberosum production would increase from 53.03 million tons in 2018 to 66.12 million tons in 2025 in India.