International Journal of Pure & Applied Bioscience (IJPAB)
Year : 2017, Volume : 5, Issue : 6
First page : (1042) Last page : (1051)
Article doi: http://dx.doi.org/10.18782/2320-7051.5838
Sugarcane Productivity in Bihar- A Forecast through ARIMA Model
Mahesh Kumar1*, Rohan Kumar Raman2 and Subhash Kumar1
1Department of Statistics, Mathematics and Computer Application
Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar -848125
2ICAR-Central Inland Fisheries Research Institute, Barrackpore, Kolkata-700120
*Corresponding Author E-mail: mahesh_smca@yahoo.co.in
Received: 5.10.2017 | Revised: 12.11.2017 | Accepted: 16.11.2017
ABSTRACT
This study is undertaken to attempt forecasting the sugarcane (Saccharum officinarum) productivity of Bihar through fitting of well-known Box Jenkins univariate Auto Regressive Integrated Moving Average (ARIMA) model. Time series data on sugarcane productivity in Bihar from 1939-40 to 2014-15 were taken from Sugarcane Research Institute (SRI)* Pusa, Bihar and Indian sugar** for the study. The data on sugarcane productivity in Bihar from the year 1940 to 2010 were utilized to build an ARIMA model and validated through five-year productivity data from 2011 to 2015. Akaike information criterion (AIC) was selected for best model selection criteria.ARIMA (0, 1, 1) model found best suitable model for sugarcane productivity in Bihar based on AIC model selection criteria. The performances of models are validated by comparing with actual values of sugarcane productivity in Bihar data. Using developed ARIMA (0, 1, 1) model, two years ahead, year 2016 and 2017 sugarcane productivity in Bihar forecasted showing increasing productivity with 4.22 % and 5.15 % prediction standard error.
Key words: Time series, ARIMA, AIC, Sugarcane productivity in Bihar, Forecasting
Data source: *Sugarcane Research Institute (SRI), Pusa, Bihar and ** Indian Sugar, 2016.
Full Text : PDF; Journal doi : http://dx.doi.org/10.18782
Cite this article: Kumar, M., Raman, R.K. and Kumar, S., Sugarcane Productivity in Bihar- A Forecast through ARIMA Model, Int. J. Pure App. Biosci. 5(6): 1042-1051 (2017). doi: doi: http://dx.doi.org/10.18782/2320-7051.5838
