期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2015
卷号：77
期号：2
页码：300-329
DOI：10.1007/s13171-015-0070-y
语种：English
出版社：Indian Statistical Institute
摘要：Using fractions of gamma and exponentially titled stable random variables this article develops a stick-breaking representation of a truncated normalized generalized gamma process. Sampling from the posterior of this process requires sampling from gamma titled stable random variables and we develop an algorithm to do so that is readily implemented in the open source software R . A Blocked Gibbs sampling algorithm for a Bayesian kernel mixture model is then described and we compare the performance of our algorithm with an algorithm recently proposed in the literature.
关键词：Normalized generalized gamma process ; Stick-breaking representation ; Gamma titled stable random variable ; Bayesian nonparametrics
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