A Real Example That Illustrates Interesting Properties of Bootstrap Bias Correction
A Real Example That Illustrates Interesting Properties of Bootstrap Bias Correction
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一个真实的例子，展示了自举偏差校正的有趣特性
DOI：
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发表时间：
2003
期刊：
影响因子：
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通讯作者：
A. Sampath
中科院分区：
文献类型：
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作者：
Daniel R. Jeske;A. Sampath
众所周知，自举偏差校正通常减少偏差并增加方差。一般预期所得均方误差将减小。我们提供了一个真实的例子，其中均方误差将减少或增加，这取决于对底层分布的假设。仅使用第一年的统计学研究生课程的概念，偏差校正估计量和均方误差公式开发一个简单的封闭形式的表达。与未校正的估计进行了比较。这个例子的内容可以作为课堂教学的基础，帮助学生生动地欣赏自助偏差校正的成果以及现代统计方法如何有助于解决真实的问题。
It is well known that bootstrap bias-correction typically reduces bias and increases variance. It is generally anticipated that the resultant mean squared error will be reduced. We provide a real-life example where the mean squared error will either decrease or increase, depending on what is assumed for an underlying distribution. Using only concepts from first-year statistics graduate school curricula, the bias-corrected estimator and its mean squared error formula are developed in a simple closed form expression. Comparisons with the uncorrected estimator are made. The content of this example can be the basis for a classroom lecture, helping students vividly appreciate both what bootstrap bias-correction accomplishes and how modern statistics methodology contributes to solving a real problem.