Stochastic Model for Sticklac Forecasting in India Lepcha Lawrence1, Gurung Bishal2,*, Paul Ranjit Kumar2, Sinha Kanchan2 1Uttar Bangla Krishi Vishwavidyalaya, Coochbehar, India 2Indian Agricultural & Statistical Research Instititute, New Delhi, India *Corresponding author: vsalrayan@gmail.com
Online published on 11 November, 2014. Abstract In the present study, we aim to devise most appropriate prediction model for India's annual sticklac production data based on Exponential Autoregressive (EXPAR) model. Statistical modelling and forecasting of agricultural time-series data plays a vital role in comprehending the underlying relationships among statistically significant variables and helping the planners in policy making. Accordingly, in this paper, a promising methodology of EXPAR family of models has been employed to describe India's annual sticklac production data that depict such cyclical fluctuations. The fitted EXPAR model captured the data in a satisfactory manner. Further, the performance of the model is compared by computing various measures of goodness-of-fit and forecast performance. We conclude that EXPAR model performs quite well for modelling as well as forecasting of the cyclical data under consideration. Top Keywords Linear, stochastic model, ARIMA, Statistical modelling, EXPAR, Forecasting, Sticklac production. Top |