首页> 外文期刊>Journal of Pure & Applied Microbiology >Statistical Modeling on Area, Production and Productivity of Cotton (Gossypium spp.) Crop for Ahmedabad Region of Gujarat State
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Statistical Modeling on Area, Production and Productivity of Cotton (Gossypium spp.) Crop for Ahmedabad Region of Gujarat State

机译:古吉拉特邦艾哈迈达巴德地区棉花(棉花)作物面积,产量和生产力的统计模型

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The present investigation was carried out to study area, production and productivity trends and growth rates of cotton crop grown in Ahmedabad Region of Gujarat State for the period 1949-50 to 2007-08 based on parametric and nonparametric regression models. In parametric models different linear, non-linear and time-series models were employed. The statistically most suited parametric models were selected on the basis of adjusted R2, significant regression co-efficient and co-efficient of determination (R2). Appropriate time-series models were fitted after judging the data for stationarity. The statistically sound model was selected on the basis of various goodness of fit criteria viz. Akaike's Information Criterion, Bayesian Information Criterion, RMSE, MAE and assumptions of normality and independence of residuals. In nonparametric regression optimum bandwidth was computed by cross-validation method. 'Epanechnikov-kernel' was used as the weight function. Nonparametric estimates of underlying growth function were computed at each and every time point. Residual analysis was carried out to test the randomness. Relative growth rates of area, production and productivity were estimated based on the best fitted trend function. None of the parametric model was found suitable to fit the trends in area, production and productivity of the cotton crop. Nonparametric regression was finally selected as the best fitted trend function for the area, production and productivity of cotton crop based on lower values of root mean square and mean absolute errors. Cotton production had increased at a rate of 2.58% which was due to combined effect of increase in area and productivity at a rate of 0.66 and 1.15 per cent per annum respectively.
机译:本研究基于参数和非参数回归模型,研究了古吉拉特邦艾哈迈达巴德地区1949-50至2007-08年间种植的棉花的面积,产量和生产率趋势以及增长率。在参数模型中,采用了不同的线性,非线性和时间序列模型。在调整后的R2,显着回归系数和确定系数(R2)的基础上选择了统计学上最合适的参数模型。在判断平稳性数据之后,拟合了适当的时间序列模型。基于拟合标准的各种优度选择统计上合理的模型。赤池的信息标准,贝叶斯信息标准,RMSE,MAE以及残差的正态性和独立性的假设。在非参数回归中,通过交叉验证方法计算出最佳带宽。 “ Epanechnikov-kernel”被用作权重函数。在每个时间点都计算了基本增长函数的非参数估计。进行残留分析以检验随机性。根据最佳拟合趋势函数估算面积,生产和生产率的相对增长率。没有一个参数模型适合于棉花种植面积,产量和生产力的趋势。最后,根据均方根值和绝对绝对值的较低值,选择非参数回归作为最适合棉花作物面积,产量和生产力的趋势函数。棉花产量以2.58%的速度增长,这是由于面积和生产率分别以每年0.66%和1.15%的速度增长的综合作用所致。

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