most citedVariance matrix priors for Dirichlet process mixture models with Gaussian kernels

2 citations · 3 across the 2 of their papers we have counts for

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2 papers

stat.ME2022★ 2 cited

Variance matrix priors for Dirichlet process mixture models with Gaussian kernels

Wei Jing, Michail Papathomas, Silvia Liverani

The Dirichlet Process Mixture Model (DPMM) is a Bayesian non-parametric approach widely used for density estimation and clustering. In this manuscript, we study the choice of prior…

stat.ME2017★ 1 cited

On the correspondence of deviances and maximum likelihood and interval estimates from log-linear to logistic regression modelling

Wei Jing, Michail Papathomas

Consider a set of categorical variables where at least one, denoted by , is binary. The log-linear model that describes the counts in the resulting contingency tab…