Estimating normal means with a conjugate style dirichlet process prior
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- Type
- article
- Published
- 1994-01-01
- Cited by
- 487
- References
- 15
- OpenAlex
- https://openalex.org/W2053405531
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:122146281
Keywords
Gibbs sampling, Dirichlet distribution, Conjugate prior, Hierarchical Dirichlet process, Convergence (economics)
References
- Bayes Estimates for the Linear Model
- Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems
- Nonparametric Bayesian bioassay including ordered polytomous response
- Bayes Methods for a Symmetric Unimodal Density and its Mode
- A Bayesian Analysis of Some Nonparametric Problems
- Computations of mixtures of dirichlet processes
- Empirical Bayes Estimation of a Binomial Parameter Via Mixtures of Dirichlet Processes
- Estimating Normal Means with a Dirichlet Process Prior
- Sampling-Based Approaches to Calculating Marginal Densities
- Bayesian Nonparametric Estimation for Incomplete Data Via Successive Substitution Sampling
- Bayesian Density Estimation and Inference Using Mixtures
- Markov Chains for Exploring Posterior Distributions
- General irreducible Markov chains and non-negative operators: List of symbols and notation
- Markov Chains for Exploring Posteior Distributions
- Bayesian Computations in Survival Models via the Gibbs Sampler
- General Irreducible Markov Chains and Non-Negative Operators.
- Survival Analysis: State of the Art
- Sampling-Based Approaches to Calculating Marginal Densities
- General irreducible Markov chains and non-negative operators: Notes and comments
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- Statistical relational learning with nonparametric Bayesian models
- Semiparametric Bayesian Models for Dynamic Earnings Data
- Bayesian Analysis of Varying Coefficient Models and Applications
- Advances in Bayesian Modelling and Computation: Spatio-Temporal Processes, Model Assessment and Adaptive MCMC
- Contribution to the Discussion of Objects on Subsets of Attributes," by Friedman and Meulman
- A Dirichlet Process Mixture Model for Spherical Data
- Nonparametric Bayesian discrete latent variable models for unsupervised learning
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- Defining Predictive Probability Functions for Species Sampling Models
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- Robust and Efficient Methods for Bayesian Finite Population Inference.
- Monitoring and Improving Markov Chain Monte Carlo Convergence by Partitioning
- Adaptive Reconfiguration Moves for Dirichlet Mixtures
- Supervised & unsupervised transfer learning
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