5 citations · 8 across the 4 of their papers we have counts for
5 papers
Markov Stick-breaking Processes
María F. Gil-Leyva, Antonio Lijoi, Ramsés H. Mena +1
Stick-breaking has a long history and is one of the most popular procedures for constructing random discrete distributions in Statistics and Machine Learning. In particular, due to…
Speeding up the ordered allocation sampler
Maria F. Gil-Leyva, Fidel Selva, Pierpaolo De Blasi
The ordered allocation sampler is a Gibbs sampler designed to explore the posterior distribution in nonparametric mixture models. It encompasses both infinite mixtures and finite m…
Gibbs sampling for mixtures in order of appearance: the ordered allocation sampler
Pierpaolo De Blasi, María F. Gil-Leyva
Gibbs sampling methods are standard tools to perform posterior inference for mixture models. These have been broadly classified into two categories: marginal and conditional method…
Stick-breaking processes with exchangeable length variables
María F. Gil-Leyva, Ramsés H. Mena
Our object of study is the general class of stick-breaking processes with exchangeable length variables. These generalize well-known Bayesian non-parametric priors in an unexplored…
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…