印度urad的建模与预测

K. Vishwajith, P. K. Sahu, Aditya Bhooshan Srivastava, Rajani Gautam
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引用次数: 0

摘要

本文采用自回归综合移动平均(ARIMA)和广义自回归条件异方差(GARCH)模型方法,对比哈尔邦、中央邦、北方邦、西孟加拉邦和印度的乌拉尔地区、生产和生产力的趋势进行了研究。从1970年到2009年的年度数据被用于预测到2020年。结果表明,ARIMA模型在所有状态下都优于GARCH模型,而辅助变量的加入在很大程度上提高了模型对产量和生产率的预测精度。此外,根据趋势分析分析表明,在研究的最近一段时间内,乌拉丁许多州的产量呈下降趋势。预测的数值可能会帮助决策者在目前与粮食和营养安全的斗争中有所作为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MODELING AND FORECASTING OF URAD IN INDIA
In this study researcher has been made to apply the autoregressive integrated moving average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model approach to investigate the trend in Urad area, production and productivity in Bihar, Madhya Pradesh, Uttar Pradesh, West Bengal, and India. Yearly data from 1970 to 2009 were used for forecasting up to 2020. In comparison, we get that in area ARIMA model outperformed GARCH model in all the states under study, whereas inclusion of auxiliary variables improve the model accuracy for production and productivity in maximum cases. Furthermore, according to the trend analysis analysis signifies that production of uradin many state has shown decreasing trend in recent period under study. Forecasted values are likely to help the policy maker in existing battle against food and nutritional security.
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