Pitman - Yor过程分层模型的截断双参数泊松-狄利克雷近似

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY Scandinavian Journal of Statistics Pub Date : 2023-09-28 DOI:10.1111/sjos.12688
Junyi Zhang, Angelos Dassios
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引用次数: 0

摘要

摘要本文通过截断Pitman-Yor过程的两参数泊松-狄利克雷表示,构造了一个近似。截断基于随机权重的递减序列,因此与流行的截断木棍断裂过程相比,具有更低的近似误差。我们开发了一种精确的模拟算法来从近似过程中采样,并为精确模拟算法变得缓慢的参数区提供了一种替代的MCMC算法。通过对Pitman-Yor过程的函数估计,证明了仿真算法的有效性。然后,我们将近似过程改编为Pitman-Yor过程混合模型,并设计了一个闭塞的Gibbs采样器进行后验推理。
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Truncated two‐parameter Poisson‐Dirichlet approximation for Pitman‐Yor process hierarchical models
Abstract In this paper, we construct an approximation to the Pitman–Yor process by truncating its two‐parameter Poisson–Dirichlet representation. The truncation is based on a decreasing sequence of random weights, thus having a lower approximation error compared to the popular truncated stick‐breaking process. We develop an exact simulation algorithm to sample from the approximation process and provide an alternative MCMC algorithm for the parameter regime where the exact simulation algorithm becomes slow. The effectiveness of the simulation algorithms is demonstrated by the estimation of the functionals of a Pitman–Yor process. Then we adapt the approximation process into a Pitman–Yor process mixture model and devise a blocked Gibbs sampler for posterior inference.
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来源期刊
Scandinavian Journal of Statistics
Scandinavian Journal of Statistics 数学-统计学与概率论
CiteScore
1.80
自引率
0.00%
发文量
61
审稿时长
6-12 weeks
期刊介绍: The Scandinavian Journal of Statistics is internationally recognised as one of the leading statistical journals in the world. It was founded in 1974 by four Scandinavian statistical societies. Today more than eighty per cent of the manuscripts are submitted from outside Scandinavia. It is an international journal devoted to reporting significant and innovative original contributions to statistical methodology, both theory and applications. The journal specializes in statistical modelling showing particular appreciation of the underlying substantive research problems. The emergence of specialized methods for analysing longitudinal and spatial data is just one example of an area of important methodological development in which the Scandinavian Journal of Statistics has a particular niche.
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