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具有尖峰—连续混合基测度的 Pitman–Yor 过程AI 解读

Summary For the most popular discrete nonparametric models, beyond the Dirichlet process, the prior guess at the shape of the data-generating distribution, also known as the base measure, is assumed to be diffuse. Such a specification greatly simplifies the derivation of analytical results, allowing for a straightforward implementation of Bayesian nonparametric inferential procedures. However, in several applied problems the available prior information leads naturally to the…

计数过程的非参数贝叶斯建模AI 解读

Data on count processes arise in a variety of applications, including longitudinal, spatial and imaging studies measuring count responses. The literature on statistical models for dependent count data is dominated by models built from hierarchical Poisson components. The Poisson assumption is not warranted in many applied contexts, and hierarchical Poisson models make restrictive assumptions about overdispersion in marginal distributions. In this article we propose a class…