The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Bayesian Density Estimation and Inference Using Mixtures
Abstract
We describe and illustrate Bayesian inference in models for density estimation using mixtures of Dirichlet processes. These models provide natural settings for density estimation and are exemplified by special cases where data are modeled as a sample from mixtures of normal distributions. Efficient simulation methods are used to approximate various prior, posterior, and predictive distributions. This allows for direct inference on a variety of practical issues, including problems of local versus global smoothing, uncertainty about density estimates, assessment of modality, and the inference on the numbers of components. Also, convergence results are established for a general class of normal mixture models.
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Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Monte Carlo sampling methods using Markov chains and their applications.
Hastings, W. K. (1970) · Biometrika · doi:10.1093/biomet/57.1.97 · Cited by 15,195
Sampling-based approaches to calculating marginal densities
Gelfand, A. E., & Smith, A. F. M. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10476213 · Cited by 6,606
Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods
Smith, A. F. M., & Roberts, G. O. (1993) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1993.tb01466.x · Cited by 1,713
Cited by
McLachlan, G., & Peel, D. (2000) · Wiley Series in Probability and Statistics · doi:10.1002/0471721182 · Cited by 10,991
An introduction to MCMC for machine learning.
Andrieu, C., de Freitas, N., Doucet, A., & Jordan, M. I. (2003) · Machine Learning · doi:10.1023/a:1020281327116 · Cited by 2,451
Hierarchical Dirichlet Processes
Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2006) · Journal of the American Statistical Association · doi:10.1198/016214506000000302 · Cited by 2,120
A Bayesian Mixture Model for Across-Site Heterogeneities in the Amino-Acid Replacement Process
Lartillot, N., & Philippe, H. (2004) · Molecular Biology and Evolution · doi:10.1093/molbev/msh112 · Cited by 1,516
Evolution and impact of subclonal mutations in chronic lymphocytic leukemia
Landau, D. A., Carter, S. L., Stojanov, P., McKenna, A., Stevenson, K., Lawrence, M. S., Sougnez, C., Stewart, C., Sivachenko, A., Wang, L., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.019 · Cited by 1,379
Metadata
- Authors
- Escobar, M. D., & West, M.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1995-06
- Volume
- 90
- Issue
- 430
- Pages
- 577-588
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2091797506
- Cited by
- 2,255
- References
- 4
- FWCI
- 20.59
- Type
- journal article
- Language
- en
- Open access
- closed
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