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Statistical model for forecasting production of ginger in India

Journal of Pharmacognosy and Phytochemistry · 2020 · Vol. 9 · pp. 317–320

Abstract

The present research study was carried out to fit different Linear, Non – Linear and ARIMA models on production of Ginger (Zingiber officinale) in India for the period 1970-71 to 2018-19. Statistically the best fitted model was chosen on the basis of goodness of fit criteria’s like R2, Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). Among all the models, ARIMA (4, 1, 2) was found to be the best fitted model for future forecasting. The results were shown, there is an increasing trend for certain long time of period and then fluctuating for short time of period and again it was increasing for a certain long time of period. It means that for a certain long time of period, the production of Ginger in India has been increasing. Based on this trend to forecast production of Ginger crop for next four years. The forecasted production of Ginger in India for the years 2019-20 to 2020-23 to be 2212.3, 2114.9, 2211.8, 2506.3 in thousand metric tonnes respectively.

Agricultural Economics and PracticesSocial and Economic Development in IndiaAutoregressive integrated moving averageMathematicsStatisticsMean absolute percentage errorProduction (economics)Mean squared errorMetric (unit)Goodness of fitToxicologyTime series
Citations
1
FWCI
0.47
field-weighted impact
References
0
Percentile
73%
vs. same field & year
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