Open Access
A constructive definition of dirichlet priors
Reads0
Chats0
About:
The article was published on 1991-01-01 and is currently open access. It has received 1560 citations till now. The article focuses on the topics: Hierarchical Dirichlet process & Constructive.read more
Citations
More filters
Proceedings ArticleDOI
Multi-document topic segmentation
Minwoo Jeong,Ivan Titov +1 more
TL;DR: An unsupervised Bayesian model is proposed for the considered problem that models both shared and document-specific topics, and utilizes Dirichlet process priors to determine the effective number of topics.
Book ChapterDOI
Consistency of Bayesian inference for survival analysis with or without censoring
TL;DR: In this article, the convergence of the posterior distribution to the true distribution in the context of survival analysis data is studied in the presence of censoring, when the prior is a Dirichlet process.
Proceedings Article
Gibbs sampling for (Coupled) infinite mixture models in the stick breaking representation
TL;DR: In this paper, Gibbs samplers for infinite complexity mixture models in the stick breaking representation are explored to improve mixing over cluster labels and to bring clusters into correspondence, and an application to modeling of storm trajectories is used to illustrate these ideas.
Journal ArticleDOI
Modeling and Clustering Positive Vectors via Nonparametric Mixture Models of Liouville Distributions
Wentao Fan,Nizar Bouguila +1 more
TL;DR: A convergence-guaranteed learning algorithm based on the averaged collapsed variational Bayes inference that can effectively learn model parameters with closed-form solutions is proposed.
Journal ArticleDOI
Non parametric mixture priors based on an exponential random scheme
Sonia Petrone,Piero Veronese +1 more
TL;DR: In this paper, a general procedure for constructing nonparametric priors for Bayesian inference is proposed, which selects absolutely continuous distribution functions, hence it can be useful with continuous data.
References
More filters
Journal ArticleDOI
A Bayesian Analysis of Some Nonparametric Problems
TL;DR: In this article, a class of prior distributions, called Dirichlet process priors, is proposed for nonparametric problems, for which treatment of many non-parametric statistical problems may be carried out, yielding results that are comparable to the classical theory.
Journal ArticleDOI
Ferguson Distributions Via Polya Urn Schemes
TL;DR: In this article, it was shown that a random probability measure P* on X has a Ferguson distribution with parameter p if for every finite partition (B1, *. *, B) of X, the vector p*(B,), * * *, p *(B) has a Dirichlet distribution with parameters (Bj), *--, cp(B,) (when p(B), = 0, this means p*) = 0 with probability 1).
Journal ArticleDOI
Implicit renewal theory and tails of solutions of random equations
TL;DR: For the solutions of certain random equations, or equivalently the stationary solutions of the random recurrences, the distribution tails are evaluated by renewal-theoretic methods as mentioned in this paper.
Book ChapterDOI
Bayesian density estimation by mixtures of normal distributions
TL;DR: In this article, a mixture of a countable number of normal distributions is used to estimate a density f(x) on the real line, which is then used for kernel estimation.
Journal ArticleDOI
On the Asymptotic Behavior of Bayes' Estimates in the Discrete Case
TL;DR: In this article, it was shown that the posterior probability converges to point mass at the true parameter value among almost all sample sequences (for short, the posterior is consistent; see Definition 1) exactly for parameter values in the topological carrier of the prior.