Sampling Some Truncated Distributions Via Rejection Algorithms
Sampling Some Truncated Distributions Via Rejection Algorithms
复制标题
通过拒绝算法对一些截断分布进行采样
DOI：
10.1080/03610918.2010.484117
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Thomas S. Shively
中科院分区：
文献类型：
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作者：
Purushottam W. Laud;P. Damien;Thomas S. Shively
在这篇文章中，我们开发了拒绝抽样算法，从一些截断和尾部分布的样本。在许多马尔可夫链蒙特卡罗方法中需要这样的采样器，通常与贝叶斯推理有关。除了单变量正态分布、伽玛分布和贝塔分布之外，我们还考虑截断到某些集合的多元正态分布。
In this article, we develop rejection sampling algorithms to sample from some truncated and tail distributions. Such samplers are needed in many Markov chain Monte Carlo methods, often in connection with Bayesian inference. In addition to univariate normal, gamma, and beta distributions, we consider multivariate normal distributions truncated to certain sets.