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Prospects of livestock and dairy production in India under time series framework.

机译:时间序列框架下印度畜牧业和奶业生产的前景。

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摘要

Share of livestock sector especially dairy production in total gross domestic product (GDP) has shown a continuous rise trend over the last 30 years. Autoregressive integrated moving average (ARIMA) methodology was applied for modeling and forecasting of milk production of India. Auto-correlation (AC) and partial auto-correlation (PAC) functions were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting the future production. A significant increasing linear trend in the total milk production in India was found. To this end, evaluation of forecasting is carried out with mean absolute prediction error (MAPE), relative mean absolute prediction error (RMAPE) and root mean square error (RMSE). The best identified model for the data under consideration was used for out-of-sample forecasting up to 2015.
机译:在过去的30年中,畜牧业特别是乳制品生产在国内生产总值中的比重呈现出持续增长的趋势。自回归综合移动平均法(ARIMA)方法用于印度牛奶产量的建模和预测。估计了自相关(AC)和部分自相关(PAC)函数,这导致了ARIMA模型的识别和构建,适合于解释时间序列和预测未来产量。在印度,牛奶的总产量呈明显的线性增长趋势。为此,使用平均绝对预测误差(MAPE),相对平均绝对预测误差(RMAPE)和均方根误差(RMSE)进行预测评估。所考虑的数据的最佳识别模型用于直至2015年的样本外预测。

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