Results 61 to 70 of about 31,307,485 (221)
Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables
Entropy, 2016 Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence.
Alessio Benavoli, Cassio P. de Campos
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Topic model for graph mining based on hierarchical Dirichlet process
Statistical Theory and Related Fields, 2020 In this paper, a nonparametric Bayesian graph topic model (GTM) based on hierarchical Dirichlet process (HDP) is proposed. The HDP makes the number of topics selected flexibly, which breaks the limitation that the number of topics need to be given in ...
Haibin Zhang, Shang Huating, Xianyi Wu
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Models beyond the Dirichlet process [PDF]
Bayesian nonparametric inference is a relatively young area of research and it has recently undergone a strong development. Most of its success can be explained by the considerable degree of exibility it ensures in statistical modelling, if compared to ...
Antonio Lijoi, Igor Pruenster
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An Integral Characterization of the Dirichlet Process [PDF]
Journal of Theoretical Probability, 2019 We give a new integral characterization of the Dirichlet process on a general phase space. To do so we first prove a characterization of the nonsymmetric Beta distribution via size-biased sampling. Two applications are a new characterization of the Dirichlet distribution and a marked version of a classical characterization of the Poisson-Dirichlet ...
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Multivariate Powered Dirichlet-Hawkes Process
, 2023 The publication time of a document carries a relevant information about its semantic content. The Dirichlet-Hawkes process has been proposed to jointly model textual information and publication dynamics. This approach has been used with success in several recent works, and extended to tackle specific challenging problems --typically for short texts or ...
Gaël Poux-Médard +2 more
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Statistica, 2015 The municipality of Milan is one of the most important areas in Italy being the center of many economic activities and the destination of strong national and international immigration.
Antonio Canale, Bruno Scarpa
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Dirichlet Process Hidden Markov Multiple Change-point Model [PDF]
, 2015 This paper proposes a new Bayesian multiple change-point model which is based on the hidden Markov approach. The Dirichlet process hidden Markov model does not require the specification of the number of change-points a priori.
S. Ko, T. Chong, Pulak Ghosh
semanticscholar +1 more source
Some diffusion processes associated with two parameter Poisson–Dirichlet distribution and Dirichlet process [PDF]
Probability Theory and Related Fields, 2009 The two parameter Poisson-Dirichlet distribution $PD(α,θ)$ is the distribution of an infinite dimensional random discrete probability. It is a generalization of Kingman's Poisson-Dirichlet distribution. The two parameter Dirichlet process $Π_{α,θ,ν_0}$ is the law of a pure atomic random measure with masses following the two parameter Poisson-Dirichlet ...
Feng, Shui, Sun, Wei
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A New Single Image Super-Resolution Method Based on the Infinite Mixture Model
IEEE Access, 2017 As a powerful nonparametric Bayesian model, the infinite mixture model has been successfully used in machine learning and computer vision. The success of the infinite mixture model owes to the capability clustering and density estimation.
Peitao Cheng +3 more
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A vector of Dirichlet processes [PDF]
Electronic Journal of Statistics, 2013 Random probability vectors are of great interest especially in view of their application to statistical inference. Indeed, they can be used for determining the de Finetti mixing measure in the representation of the law of a partially exchangeable array of random elements taking values in a separable and complete metric space.
Leisen, Fabrizio +2 more
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