A tutorial on Dirichlet process mixture modeling

DOI10.1016/j.jmp.2019.04.004zbMath1431.62548OpenAlexW2945591580WikidataQ92886212 ScholiaQ92886212MaRDI QIDQ2332845

Mithat Gönen, Yuelin Li, Elizabeth Schofield

Publication date: 5 November 2019

Published in: Journal of Mathematical Psychology (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6583910

zbMATH Keywords

Dirichlet processGibbs samplingmixture modelChinese restaurant processBayesian nonparametric

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric estimation (62G05) Applications of statistics to psychology (62P15)

Related Items (1)

Calibrating generative models: the probabilistic Chomsky-Schützenberger hierarchy

Uses Software

• Scikit
• DPpackage
• BayesDA
• Bayesian Regression

Cites Work

• A tutorial on Bayesian nonparametric models
• Theory and computations for the Dirichlet process and related models: an overview
• Generating random correlation matrices based on vines and extended onion method
• A Bayesian nonparametric approach to test equating
• Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
• Ferguson distributions via Polya urn schemes
• Bayesian nonparametric data analysis
• Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling
• Modeling individual differences using Dirichlet processes
• A Bayesian analysis of some nonparametric problems
• Dealing With Label Switching in Mixture Models
• Bayesian Density Estimation and Inference Using Mixtures
• Encyclopedia of Machine Learning and Data Mining
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