非对称拉普拉斯分布规范下同步回归分位数的全贝叶斯估计

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2019-06-02 DOI:10.1155/2019/8610723

Josephine Merhi Bleik

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引用次数: 4

摘要

在本文中，我们感兴趣的是通过贝叶斯方法在回归环境中同时估计几个分位数。假设误差项具有不对称拉普拉斯分布，并利用该分布的两个不同分位数之间的关系，我们提出了一种简单的完全贝叶斯方法，该方法满足分位数的非交叉性质。为了实现，我们在吉布斯算法中使用Metropolis Hastings对未知参数的全条件分布进行采样。模拟示例显示了基础方法与其他替代方法的性能和竞争力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fully Bayesian Estimation of Simultaneous Regression Quantiles under Asymmetric Laplace Distribution Specification

In this paper, we are interested in estimating several quantiles simultaneously in a regression context via the Bayesian approach. Assuming that the error term has an asymmetric Laplace distribution and using the relation between two distinct quantiles of this distribution, we propose a simple fully Bayesian method that satisfies the noncrossing property of quantiles. For implementation, we use Metropolis-Hastings within Gibbs algorithm to sample unknown parameters from their full conditional distribution. The performance and the competitiveness of the underlying method with other alternatives are shown in simulated examples.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.