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引用次数: 0
摘要
本文提出了一种双 Pólya-Gamma 数据扩增方案,用于从总体和分类计数数据的贝叶斯分层模型中进行后验采样。该方案适用于带有对数链接和回归系数正态先验的负二项-二项(NBB)分层回归模型。结果表明,该方法非常高效,在大多数情况下都优于 Stan 程序。分层建模框架和 Pólya-Gamma 数据增强方案被应用于人类线粒体 DNA 数据。
A double Pólya-Gamma data augmentation scheme for a hierarchical Negative Binomial - Binomial data model
A double Pólya-Gamma data augmentation scheme is developed for posterior sampling from a Bayesian hierarchical model of total and categorical count data. The scheme applies to a Negative Binomial - Binomial (NBB) hierarchical regression model with logit links and normal priors on regression coefficients. The approach is shown to be very efficient and in most cases out-performs the Stan program. The hierarchical modeling framework and the Pólya-Gamma data augmentation scheme are applied to human mitochondrial DNA data.
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.