Forecasting of yield and production of groundnut using ARIMAX
Author(s):
Neelam Chouksey
Abstract:
Historical data has been considered for forecasting of groundnut yield and production. For the purpose, autoregressive integrated moving average with explanatory variables has been applied along with all estimation procedures. There are ARIMAX technique employed for forecasting of groundnut yield and production on time based data of Surguja district of Chhattisgarh. Data of Weather variables viz. maximum temperature, minimum temperature rainfall and Precipitation (1966 to 2020) is taken from Meteorological observatory of Rajmohini Devi College of, Agriculture and Research Station Ambikapur, Chhattisgarh as input variables in ARIMAX model. Comparative study of the fitted models is carried out from the viewpoint of mean absolute percentage error (MAPE), root mean squared error (RMSE). After comparison resulted that ARIMAX (1,1,1) and ARIMAX (1,1,0) model provided a lower RMSE from other models for yield and production respectively.
How to cite this article:
Neelam Chouksey. Forecasting of yield and production of groundnut using ARIMAX. The Pharma Innovation Journal. 2021; 10(11S): 529-533.