Feb. 13, 2024, 5:46 a.m. | Changwoo J. Lee Alessandro Zito Huiyan Sang David B. Dunson

stat.ML updates on arXiv.org arxiv.org

The beta distribution serves as a canonical tool for modeling probabilities and is extensively used in statistics and machine learning, especially in the field of Bayesian nonparametrics. Despite its widespread use, there is limited work on flexible and computationally convenient stochastic process extensions for modeling dependent random probabilities. We propose a novel stochastic process called the logistic-beta process, whose logistic transformation yields a stochastic process with common beta marginals. Similar to the Gaussian process, the logistic-beta process can model dependence …

bayesian beta canonical distribution extensions machine machine learning modeling process processes random statistics stat.me stat.ml stochastic stochastic process tool work

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