Multiscale stick-breaking mixture models

DOI10.1007/s11222-020-09991-1zbMath1461.62023arXiv2001.05729OpenAlexW3121954085MaRDI QIDQ2029098

Marco Stefanucci, Antonio Canale

Publication date: 3 June 2021

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2001.05729

zbMATH Keywords

Bayesian nonparametricsDirichlet processdensity estimationPitman-Yor processPólya trees

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Density estimation (62G07)

Uses Software

• DPpackage

Cites Work

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• Bayesian inference with dependent normalized completely random measures
• Computationally tractable approximate and smoothed Polya trees
• Slice sampling mixture models
• On a class of Bayesian nonparametric estimates: I. Density estimates
• Optional Pólya tree and Bayesian inference
• Size-biased sampling of Poisson point processes and excursions
• Exact mean integrated squared error
• Polya trees and random distributions
• Some aspects of Pólya tree distributions for statistical modelling
• The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator
• Distributional results for means of normalized random measures with independent increments
• More aspects of Pólya tree distributions for statistical modelling
• Normalized random measures driven by increasing additive processes
• A Bayesian analysis of some nonparametric problems
• Default priors for density estimation with mixture models
• Bayesian Kernel Mixtures for Counts
• Conjugacy as a Distinctive Feature of the Dirichlet Process
• Shared kernel Bayesian screening
• Density Estimation With Confidence Sets Exemplified by Superclusters and Voids in the Galaxies
• Posterior Analysis for Normalized Random Measures with Independent Increments
• Bayesian density estimation using bernstein polynomials
• Gibbs Sampling Methods for Stick-Breaking Priors
• Bayesian Density Estimation and Inference Using Mixtures
• Random Bernstein Polynomials
• Robustifying Bayesian nonparametric mixtures for count data
• Multiscale Bernstein polynomials for densities

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