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A constructive definition of dirichlet priors
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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
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Journal ArticleDOI
Random Partition Models with Regression on Covariates.
TL;DR: This work discusses some alternative approaches that have been used in the recent literature to implement random partition models, with an emphasis on a recently proposed extension of product partition models.
Journal ArticleDOI
Tractography segmentation using a hierarchical Dirichlet processes mixture model.
TL;DR: A new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model that does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects.
Journal ArticleDOI
Simplex Factor Models for Multivariate Unordered Categorical Data
TL;DR: A novel class of simplex factor models is proposed that scales well with increasing dimension, with the number of factors treated as unknown, and an efficient proposal for updating the base probability vector in hierarchical Dirichlet models is developed.
Journal ArticleDOI
Bayesian semiparametric joint models for functional predictors.
Jamie L. Bigelow,David B. Dunson +1 more
TL;DR: A semiparametric Bayesian approach for assessing the relationship between functional predictors and a response is proposed and it is found that the model successfully predicts early pregnancy loss.
Proceedings ArticleDOI
Beyond activity recognition: skill assessment from accelerometer data
Aftab Khan,Sebastian Mellor,Eugen Berlin,Robin Thompson,Roisin McNaney,Patrick Olivier,Thomas Plötz +6 more
TL;DR: A framework for skill assessment in activity recognition that enables automatic quality analysis of human activities and is based on a hierarchical rule induction technique that effectively abstracts from noise-prone activity data and assesses activity data at different temporal contexts is proposed.
References
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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.