Yang Cheng1, Dehua Li1,*, Wenbin Jiang 2
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 49-82, 2019, DOI:10.32604/cmes.2019.07657
Abstract Beta Process is a typical nonparametric Bayesian model. and the Beta Bernoulli Process provides a Bayesian nonparametric prior for models involving collections of binary valued features. Some previous studies considered the Beta Process inference problem by giving the Stick-Breaking sampling method. This paper focuses on analyzing the form of precise probability distribution based on a Stick-Breaking approach, that is, the joint probability distribution is derived from any finite number of observable samples: It not only determines the probability distribution function of the Beta Process with finite observation (represented as a group of number between [0,1]), More >
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