Growth Rate Estimation of Rabi Pulse Production of Odisha by Using Spline Regression Technique

Rakesh Kumar Rout, A. Dash
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Abstract

Pulses are considered to be important crop for ensuring nutritional security in Odisha. Proper estimation of growth rate in production of pulse crops allows for more effective cropping system planning and formulation of the agricultural policy of the state. To capture any abrupt changes and the variation in data in different phases of a long time period, spline regression technique is used as it can fit different models in different segments of the time period as necessary without losing the continuity of the model. The present study deals with the estimation of growth rate of area, yield and production of all rabi pulses in Odisha by using best fit spline regression model. To fit the spline regression model, the entire period of study is divided into different segments based on the scatter plot diagram which is further confirmed by testing the significance of change in coefficient of variation between the consecutive segments by chi square test. The regression model found to be suitable from the study of scatter plot of data are linear, compound, logarithmic, power, quadratic and cubic model. The best fit model is selected on the basis of error assumption test and model fit statistics such as R2, adjusted R2 and Mean Absolute Percentage error (MAPE). The respective selected best fit model is used for the estimation of growth rates of area, yield and production of rabi pulses in Odisha for each segment and the whole period of study. Among the spline regression models, the respective linear spline regression model is found to be best fit for area, yield and production of rabi pulses and are used for growth rate estimation of these variables. It is found that though the growth rate in area and yield of rabi pulses are not significant, the growth rate of production is found to be significant for the whole period of study which shows that the interaction effect of area and yield on production seems to dominate.
用样条回归估计奥里萨邦拉比脉冲产量的增长率
豆类被认为是确保奥里萨邦营养安全的重要作物。正确估计脉冲作物的产量增长率,有助于更有效地规划种植制度和制定国家的农业政策。为了捕捉任何突变和数据在长时间内不同阶段的变化,使用样条回归技术,因为它可以根据需要在不同时间段拟合不同的模型,而不会失去模型的连续性。本文采用最佳拟合样条回归模型对奥里萨邦所有拉比豆类的面积、产量和产量的增长率进行了估计。为了拟合样条回归模型,我们根据散点图将整个研究时期划分为不同的段,通过卡方检验检验连续段之间变异系数变化的显著性,进一步证实了这一点。从数据散点图的研究中发现适合的回归模型有线性模型、复合模型、对数模型、幂模型、二次模型和三次模型。根据误差假设检验和模型拟合统计量如R2、调整后的R2和平均绝对百分比误差(MAPE)来选择最佳拟合模型。分别选择的最佳拟合模型用于估计奥里萨邦每段和整个研究期间拉比豆类的面积、产量和产量的增长率。在样条回归模型中,发现各自的线性样条回归模型最适合拉比豆类的面积、产量和产量,并用于这些变量的增长率估计。结果表明,虽然面积和产量的增长率不显著,但产量的增长率在整个研究期间都是显著的,表明面积和产量的交互作用对产量的影响似乎占主导地位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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