Predictive construction of priors in Bayesian nonparametrics
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Publication:447985
DOI10.1214/11-BJPS176zbMath1319.62075arXiv1406.5421MaRDI QIDQ447985
Publication date: 30 August 2012
Published in: Brazilian Journal of Probability and Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1406.5421
exchangeabilityDirichlet processrandom probability measuresmixtures of Markov chainsurn schemesinfinite hidden Markov models
Nonparametric estimation (62G05) Bayesian inference (62F15) Research exposition (monographs, survey articles) pertaining to statistics (62-02)
Related Items (7)
Asymptotics of certain conditionally identically distributed sequences ⋮ Bayesian Predictive Inference Without a Prior ⋮ On a class of prior distributions that accounts for uncertainty in the data ⋮ A class of models for Bayesian predictive inference ⋮ Unnamed Item ⋮ The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes. ⋮ Infinite-color randomly reinforced urns with dominant colors
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
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- Unnamed Item
- Unnamed Item
- Hierarchical reinforced urn processes
- A note on extendibility and predictivistic inference in finite populations
- Bayesian analysis of variable-order, reversible Markov chains
- A sticky HDP-HMM with application to speaker diarization
- Stick-breaking autoregressive processes
- Pólya-like urns and the Ewens' sampling formula
- Nonparametric Bayes estimators based on beta processes in models for life history data
- W. E. Johnson's sufficientness postulate
- De Finetti's theorem for Markov chains
- Representations for partially exchangeable arrays of random variables
- Size-biased sampling of Poisson point processes and excursions
- Mixtures of Dirichlet processes with applications to Bayesian nonparametric problems
- Extendibility of spherical matrix distributions
- Conjugate priors for exponential families
- Characterizing Markov exchangeable sequences
- A predictivistic interpretation of the multivariate \(t\)-distribution
- The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator
- Beta-stacy processes and a generalization of the Pólya-Urn scheme
- A note on the Dirichlet process prior in Bayesian nonparametric inference with partial exchangeability
- A Glivenko-Cantelli theorem for exchangeable random variables
- Ferguson distributions via Polya urn schemes
- A bivariate Dirichlet process.
- Distributional results for means of normalized random measures with independent increments
- De Finetti's contribution to probability and statistics
- On mixtures of distributions of Markov chains.
- Nonparametric Bayesian data analysis
- Predictivistic characterizations of multivariate Student-\(t\) models
- Tailfree and neutral random probabilities and their posterior distributions
- Bayesian nonparametrics
- Urn schemes and reinforced random walks.
- Exchangeable and partially exchangeable random partitions
- On some characterizations of the \(t\)-distribution
- A Bayesian nonparametric estimator of a multivariate survival function
- Bayesian analysis for reversible Markov chains
- Completely random measures
- The sampling theory of selectively neutral alleles
- A Bayesian analysis of some nonparametric problems
- On the support of MacEachern's dependent Dirichlet processes and extensions
- Hybrid Dirichlet Mixture Models for Functional Data
- A NONPARAMETRIC URN-BASED APPROACH TO INTERACTING FAILING SYSTEMS WITH AN APPLICATION TO CREDIT RISK MODELING
- The Representation of Partition Structures
- Hierarchical Dirichlet Processes
- Bayesian Nonparametrics
- Spherical symmetry: An elementary justification
- A bayesian predictive approach to sequential search for an optimal dose: Parametric and nonparametric models
- Bayesian Clustering and Product Partition Models
- Gibbs Sampling Methods for Stick-Breaking Priors
- Estimating normal means with a conjugate style dirichlet process prior
- Bayesian Density Estimation and Inference Using Mixtures
- On random sequences with spherical symmetry
- Invariants Under Mixing Which Generalize de Finetti's Theorem: Continuous Time Parameter
- Probabilistic Symmetries and Invariance Principles
- Hierarchical Mixture Modeling With Normalized Inverse-Gaussian Priors
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