A STOCHASTIC PROCESS IN MODELING AND FORECASTING OF ONION PRODUCTION IN INDIA
Keywords:ARIMA, ACF, PACF, Onion forecast
This work focuses on modeling and analysis of crop yield over space and time. Specifically, the onion yield data set was used. This study on estimating the future yield of onions in major producing states in India. To achieve this, we applied time series on onion yield data recorded from 1978 to 2020, as per availability from the website of Ministry of Agriculture, Government of India. By using SPSS software, The data are analyzed using the autoregressive integrated moving average (ARIMA) model to best fit the model. Selected best models were used to estimate onion yield. The selection of a suitable model requires determining the efficiency of different models in predicting future outcomes and selecting the most suitable model for the prediction work. To develop a suitable forecast ARIMA model for agricultural data. To study the predictive ability of the univariate ARIMA model to suggest an optimal model, the best predictive model was selected.
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