11 citations · 19 across the 6 of their papers we have counts for
8 papers
Exact two-stage finite-mixture representations for species sampling processes
Ramsés H. Mena, Christos Merkatas, Theodoros Nicoleris +1
Discrete random probability measures are central to Bayesian inference, particularly as priors for mixture modeling and clustering. A broad and unifying class is that of proper spe…
Beta-Binomial stick-breaking non-parametric prior
María F. Gil-Leyva, Ramsés H. Mena, Theodoros Nicoleris
A new class of nonparametric prior distributions, termed Beta-Binomial stick-breaking process, is proposed. By allowing the underlying length random variables to be dependent throu…
Inference for a constrained parameter in presence of an uncertain constraint
Éric Marchand, Theodoros Nicoleris
We describe a hierarchical Bayesian approach for inference about a parameter lower-bounded by with uncertain , derive some basic identities for posterior analysis about…
Dependent Mixtures of Geometric Weights Priors
Spyridon J. Hatjispyros, Christos Merkatas, Theodoros Nicoleris +1
A new approach on the joint estimation of partially exchangeable observations is presented by constructing pairwise dependence between random density functions, each of which i…
Distributional Results Relating to the Posterior of a Dirichlet Process Prior
Spyridon J. Hatjispyros, Theodoros Nicoleris, Stephen G. Walker
The aim of this paper is to find distributional results for the posterior parameters which arise in the Sethuraman (1994) representation of the Dirichlet process. These results can…
Dependent Random Density Functions with Common Atoms and Pairwise Dependence
Spyridon J. Hatjispyros, Theodoros Nicoleris, Stephen G. Walker
The paper is concerned with constructing pairwise dependence between random density functions each of which is modeled as a mixture of Dirichlet process model. The key to this…