检索结果-内蒙古大学图书馆

Improving the data Augmentation algorithm in the two-block Setup

JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2015年第4期24卷 1114-1133页

作者： Pal, Subhadip Khare, Kshitij Hobert, James P. Univ Florida Dept Stat Gainesville FL 32611 USA

The data augmentation (da) approach to approximate sampling from an intractable probability density f(X) is based on the construction of a joint density, f(X, Y), whose conditional densities, f(X|Y) and f(Y|X), can be straightforwardly sampled. However, many applications of the da algorithm do not fall in this single-block setup. In these applications, X is partitioned into two components, X = (U, V), in such a way that it is easy to sample from f(Y|X), f(U|V, Y), and f(V|U, Y). We refer to this alternative version of da, which is effectively a three-variable Gibbs sampler, as two-block da. We develop two methods to improve the performance of the da algorithm in the two-block setup. These methods are motivated by the Haar PX-da algorithm, which has been developed in previous literature to improve the performance of the single-block da algorithm. The Haar PX-da algorithm, which adds a computationally inexpensive extra step in each iteration of the da algorithm while preserving the stationary density, has been shown to be optimal among similar techniques. However, as we illustrate, the Haar PX-da algorithm does not lead to the required stationary density f(X) in the two-block setup. Our methods incorporate suitable generalizations and modifications to this approach, and work in the two-block setup. A theoretical comparison of our methods to the two-block da algorithm, a much harder task than the single-block setup due to nonreversibility and structural complexities, is provided. We successfully apply our methods to applications of the two-block da algorithm in Bayesian robit regression and Bayesian quantile regression. Supplementary materials for this article are available online.

关键词： data augmentation algorithm Group action Haar measure Sandwich algorithm two-block da algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：