An application of ARIMAX model for forecasting of castor production in India
AN APPLICATION OF ARIMAX MODEL FOR FORECASTING OF CASTOR PRODUCTION IN INDIA
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Authors
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R VIJAYA KUMARI
College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad-500 030, Telangana
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G RAMAKRISHNA
College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad-500 030, Telangana
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VENKATESH PANASA
College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad-500 030, Telangana
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A SREENIVAS
College of Agriculture, Professor Jayashankar Telangana State Agricultural University, Hyderabad-500 030, Telangana
Keywords:
ARIMAX model, Forecasting, Mean absolute percentage error, Partial autocorrelation functionsAbstract
When an ARIMA model includes other time series as input variables, the model is referred to as an ARIMAX model. The autoregressive integrated moving average with exogenous variable (ARIMAX) model can take the impact of covariates on the forecasting into account, improving the comprehensiveness and accuracy of the prediction. In this paper, ARIMAX model has been applied to forecast castor production in India which includes time series data on rainfall as input exogenous variable. ARIMAX (111) is found to be the best model for future projections of castor production in India. The analysis of 53 years data from 1966-67 to 2018-19 predicted that castor production may increase to 1547.05 thousand tonnes by the year 2020-21 and 1674.90 thousand tonnes by the year 2021-22.
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