Validation of Growth Rate Estimate Using Spline Regression Technique for Green Gram Production in Odisha

IF 0.3 Q4 ECONOMICS
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引用次数: 0

Abstract

The varying pattern of agriculture data in different phases over a long period could be thought of capturing effectively by the spline regression technique. The present study focuses on using spline regression in estimating the growth rate of production of green gram for Odisha. This technique requires the segmentation of the entire study period into distinct periods by inserting knots at suitable intervals. It ensures the same pattern of variation in a particular segment and an abrupt change in the pattern of variation in the next segment. The spline regression approach was compared to the conventional regression technique based on specific statistical criteria to confirm its performance. To estimate the growth rate of green gram in Odisha, spline regression models outperformed conventional regression models, which is why they were chosen for the first and last segments of the study period for area, yield, and output. Keywords: Continuity, growth rate, knot, segment, spline regression. JEL Codes: B23, C32, G21.
用样条回归技术估计奥里萨邦绿克产量的生长速率验证
样条回归技术可以有效地捕捉长时期内不同阶段农业数据的变化规律。本研究的重点是利用样条回归估计奥里萨邦绿克产量的增长率。这种技术需要在适当的间隔插入结,将整个研究时期分割成不同的时期。它保证了在一个特定片段中相同的变化模式和下一个片段中变化模式的突变。基于特定的统计准则,将样条回归方法与传统回归方法进行了比较,以验证其性能。为了估计奥里萨邦绿克的生长速度,样条回归模型优于传统的回归模型,这就是为什么在研究期间的第一个和最后一个阶段选择样条回归模型来计算面积、产量和产量。关键词:连续性,增长率,结,段,样条回归。JEL代码:B23, C32, G21。
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CiteScore
0.50
自引率
50.00%
发文量
66
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