| 基于贝叶斯的Bootstrap置信区间 |
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| 引用本文： | 张茺喨,田茂再.基于贝叶斯的Bootstrap置信区间[J].统计与决策,2020(1):32-35. |
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| 作者姓名： | 张茺喨 田茂再 |
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| 作者单位： | 兰州财经大学统计学院;中国人民大学应用统计科学研究中心;中国人民大学统计学院 |
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| 基金项目： | 国家自然科学基金资助项目(11861042) |
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| 摘 要： | 在许多领域中,Bootstrap成为一种数据处理的有效方法。很多情况下,模型中感兴趣的参数的置信区间难以构建,为了解决这一问题,文章提出了一个新的贝叶斯Bootstrap置信区间的估计量,并做了蒙特卡洛模拟比较,结果比经典区间估计方法和经典Bootstrap方法更优,并进行了实例分析。
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| 关 键 词： | BOOTSTRAP 贝叶斯 置信区间 |
Bootstrap Confidence Interval Based on Bayes |
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| Authors: | Zhang Chongliang Tian Maozai |
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| Institution: | (School of Statistics,Lanzhou University of Finance and Economics,Lanzhou 730020,China;Center for Applied Statistics,Renmin University of China,Beijing 100872,China;School of Statistics,Renmin University of China,Beijing 100872,China) |
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| Abstract: | Bootstrap is an effective method for data processing in many fields,but in many cases,confidence intervals for parameters of interest in the model are difficult to construct.In order to solve the problem,this paper proposes a new estimator of Bayesian Bootstrap confidence interval,and makes a Monte Carlo simulation comparison,whose results are better than those of the classical interval estimation method and the classical Bootstrap method.Finally examples are giver for analysis. |
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| Keywords: | Bootstrap Bayes confidence interval |
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