At present, there are three main implementations of Nonparametrics Bayes model in machine learning: Dirichlet Process and CRP model, Beta Process and Beta Bernouilli Process model, Gamma Process and Gamma Poisson Process model. Aiming at the infinite sampling process constructed by Gamma Process Stick Breaking proposed by Anirban Roychowdhury, this paper discusses the problem of exact inference based on a finite number of observation samples, analyzes the exact probability distribution function of Gamma Process Stick Breaking construction, and takes this distribution function as a priori, and applies the corresponding results to the inference of Gamma Poisson process.
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Inference and sampling of gamma poisson process stick breaking construction model
Semantic Scholar · Mathematics · 2020
Abstract
At present, there are three main implementations of Nonparametrics Bayes model in machine learning: Dirichlet Process and CRP model, Beta Process and Beta Bernouilli Process model, Gamma Process and Gamma Poisson Process model. Aiming at the infinite sampling process constructed by Gamma Process Stick Breaking proposed by Anirban Roychowdhury, this paper discusses the problem of exact inference based on a finite number of observation samples, analyzes the exact probability distribution function of Gamma Process Stick Breaking construction, and takes this distribution function as a priori, and applies the corresponding results to the inference of Gamma Poisson process.