发帖
雷达卡
摘要翻译：
引导是一种通过重新采样数据或从数据估计的模型来估计估计量或测试统计量的分布的方法。在各种计量经济学应用中成立的条件下，bootstrap提供了统计分布的近似，置信区间的复盖概率和假设检验的拒绝概率，这些近似比一阶渐近分布理论的近似更精确。真实复盖率和名义复盖率之间的差异或拒绝概率的减少可能非常大。此外，bootstrap提供了一种在某些情况下进行推理的方法，在这些情况下获得解析分布近似是困难或不可能的。这篇文章解释了在计量经济学感兴趣的上下文中引导的有用性和局限性。演示文稿是非正式的和说明性的。它提供了对引导程序如何工作的直观理解。数学细节可在引用的参考文献中获得。
---
英文标题：
《Bootstrap Methods in Econometrics》
---
作者：
Joel L. Horowitz
---
最新提交年份：
2018
---
分类信息：
一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
--
---
英文摘要：
The bootstrap is a method for estimating the distribution of an estimator or test statistic by re-sampling the data or a model estimated from the data. Under conditions that hold in a wide variety of econometric applications, the bootstrap provides approximations to distributions of statistics, coverage probabilities of confidence intervals, and rejection probabilities of hypothesis tests that are more accurate than the approximations of first-order asymptotic distribution theory. The reductions in the differences between true and nominal coverage or rejection probabilities can be very large. In addition, the bootstrap provides a way to carry out inference in certain settings where obtaining analytic distributional approximations is difficult or impossible. This article explains the usefulness and limitations of the bootstrap in contexts of interest in econometrics. The presentation is informal and expository. It provides an intuitive understanding of how the bootstrap works. Mathematical details are available in references that are cited.
---
PDF链接：
https://arxiv.org/pdf/1809.04016
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
京公网安备 11010802022788号
