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首页> 外文期刊>International Journal of Statistical Distributions and Applications >Comparing Parameter Estimates Obtained by Simulation Study and Real Life Data from the Two-Parameter Gamma Model
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Comparing Parameter Estimates Obtained by Simulation Study and Real Life Data from the Two-Parameter Gamma Model

机译:通过仿真研究获得的参数估计值与两参数Gamma模型的实际数据进行比较

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The aim of this study was to employ Maximum Likelihood (MLE) jointly with a numerical Method (Newton Raphson method) to obtain parameter estimates from the two-parameter Gamma model. The profile likelihood of the twoparameter Gamma model was also put into consideration. The methods were demonstrated using simulation studies and real life data considering data sets generated by R statistical software for different sample sizes. Standard errors were computed and 5 % Wald-confidence interval was constructed for the estimates of the model. The result of the study shows that Maximum Likelihood Estimation (MLE) jointly with Newton Raphson method was more efficient for estimating parameters of the Gamma model in simulation study than real life data. The study recommends that parameter estimates from the two-parameter Gamma model should be obtained by employing Maximum Likelihood Estimation jointly with Newton Raphson Method.
机译:这项研究的目的是将最大似然(MLE)与数值方法(Newton Raphson方法)结合使用,以从两参数Gamma模型获得参数估计值。还考虑了双参数Gamma模型的轮廓似然性。考虑到由R统计软件针对不同样本量生成的数据集,通过模拟研究和现实生活数据证明了这些方法。计算标准误差,并为模型的估计构建5%Wald置信区间。研究结果表明,与真实数据相比,最大似然估计(MLE)与牛顿拉弗森方法的结合在模拟研究中更有效地估计Gamma模型的参数。研究建议应通过采用牛顿拉夫森法联合使用最大似然估计来获得两参数伽玛模型的参数估计。

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