Robustifying Bayesian nonparametric mixtures for count data
From MaRDI portal
Publication:5347416
DOI10.1111/biom.12538zbMath1366.62205OpenAlexW2343968659WikidataQ31086766 ScholiaQ31086766MaRDI QIDQ5347416
Publication date: 23 May 2017
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/2318/1609944
Bayesian nonparametricsPoisson mixturemixture modelPitman-Yor processabundance heterogeneityrounded mixture of Gaussians
Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)
Related Items (6)
Importance conditional sampling for Pitman-Yor mixtures ⋮ A Robustified Posterior for Bayesian Inference on a Large Number of Parallel Effects ⋮ A Common Atoms Model for the Bayesian Nonparametric Analysis of Nested Data ⋮ On a Dirichlet process mixture representation of phase-type distributions ⋮ Multiscale stick-breaking mixture models ⋮ Low information omnibus (LIO) priors for Dirichlet process mixture models
Uses Software
Cites Work
- Bayesian semiparametric inference for multivariate doubly-interval-censored data
- On a class of Bayesian nonparametric estimates: I. Density estimates
- The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator
- Bayesian nonparametric data analysis
- Bayesian Kernel Mixtures for Counts
- Mixed Poisson Distributions
- Modeling Unobserved Sources of Heterogeneity in Animal Abundance Using a Dirichlet Process Prior
- Bayesian Nonparametric Estimation of the Probability of Discovering New Species
- A semiparametric Bayesian model for randomised block designs
- Analysis of Overdispersed Count Data by Mixtures of Poisson Variables and Poisson Processes
- Bayesian Analysis of Poisson Mixtures
- Gibbs Sampling Methods for Stick-Breaking Priors
- Bayesian Density Estimation and Inference Using Mixtures
- A New Estimator of the Discovery Probability
- Hierarchical Mixture Modeling With Normalized Inverse-Gaussian Priors
- Modeling with normalized random measure mixture models
This page was built for publication: Robustifying Bayesian nonparametric mixtures for count data
