用于分析印度部分邦小麦产量增长和趋势模式的统计模型

Manish Kumar, Gyan Prakash, Shiv Kumar Rana
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引用次数: 0

摘要

本文通过拟合著名的统计模型,即线性模型、指数模型和立方模型,对印度一些选定邦的小麦产量进行了时间序列分析。选择小麦种植邦的标准是产量较高和增长模式一致。小麦产量的二级时间序列数据被用于分析。在拟合相关模型时计算了趋势值,并使用卡方检验统计量对模型的有效性进行了检验。此外,还计算了判定系数()、均方根误差(RMSE)和相对平均绝对百分比误差(RMAPE),以揭示相关模型是否适合用于探索印度相关邦的小麦生产趋势模式。调查结果显示,上述模型适用于预测相关邦小麦生产的未来趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Modeling for Analysis of Growth and Trend Pattern of Wheat Production in Selected States of India
In the present paper, the time series analysis of wheat production in some selected states of India has been carried out by fitting well-known statistical models, viz. linear, exponential and cubic models. The selection of wheat growing states has been made on the basis of criteria of higher production and consistent growth pattern. The secondary time series data on wheat production have been utilized for the analysis. The trend values have been computed on fitting the concerned models, and the validity of the models has been tested on using the chi-square test statistic. Moreover, the coefficient of determination ( ), root mean square error (RMSE), and relative mean absolute percentage error (RMAPE) have been computed to reveal the suitability of the concerned models for exploring the trend patterns of wheat production in the concerned states of India. The findings of the investigation reveal that the above mentioned models are appropriate for forecasting of future trend of wheat production in the concerned states.
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