A Sequential Algorithm for Fast Fitting of Dirichlet Process Mixture Models

Journal of Computational and Graphical Statistics

Volumn 23, Issue 4, 2014, Pages 1143-1162

  Zhang, Xiaole ^a   Nott, David J ^b   Yau, Christopher ^a   Jasra, Ajay ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Approximate Bayesian inference; Density estimation; Mixture modeling; Variational Bayes

Indexed keywords

EID: 84908074448     PISSN: 10618600     EISSN: 15372715     Source Type: Journal    
DOI: 10.1080/10618600.2013.870906     Document Type: Article

References (20)

1. Bishop, C.M. (2006), Pattern Recognition and Machine Learning, New York: Springer.
2. Blackwell, D., Macqueen, J.B. (1973), Ferguson Distributions via Pólya Schemes, The Annals of Statistics, 1, 353–355.
3. Blei, D.M., Jordan, M.I. (2006), Variational Inference for Dirichlet Process Mixtures, Bayesian Analysis, 1, 121–144.
4. Bush, C.A., MacEachern, S.N. (1996), A Semiparametric Bayesian Model for Randomized Block Designs, Biometrika, 83, 275–285.
5. Chan, C., Feng, F., Ottinger, J., Foster, D., West, M., Kepler, T. (2008), Statistical Mixture Modeling for Cell Subtype Identification in Flow Cytometry, Cytometry A, 73, 693–701.
6. Escobar, M.D., West, M. (1995), Bayesian Density Estimation and Inference Using Mixtures, Journal of the American Statistical Association, 90, 577–588.
7. Ferguson, T.S. (1973), A Bayesian Analysis of Some Nonparametric Problems, The Annals of Statistics, 1, 209–230.
8. Giannoulatou, E., (2008), GenoSNP: A Variational Bayes Within-Sample SNP Genotyping Algorithm That Does not Require a Reference Population, Bioinformatics, 24, 2209–2214.
9. Ishwaran, H., James, L.F. (2001), Gibbs Sampling Methods for Stick-Breaking Priors, Journal of the American Statistical Association, 96, 161–173.
10. Jasra, A., Holmes, C.C., Stephens, D.A. (2005), Markov Chain Monte Carlo and the Label Switching Problem in Bayesian Mixture Modelling, Statistical Science, 20, 50–67.
11. Jordan, M.I., Ghahramani, Z., Jaakkola, T.S., and Saul, L.K. (1999), “An Introduction to Variational Methods for Graphical Models,” in Learning in Graphical Models, ed. M. I. Jordan, Cambridge: MIT Press.
12. Lo, A.Y. (1984), On a Class of Bayesian Nonparametric Estimation: I. Density Estimates, The Annals of Statistics, 12, 351–357.
13. MacEachern, S.N. (1994), Estimating Normal Means With a Conjugate Style Dirichlet Process Prior, Communications in Statistics—Simulation, 23, 727–741.
14. MacEachern, S.N., Müller, P. (1998), Estimating Mixture of Dirichlet Process Models, Journal of Computational and Graphical Statistics, 7, 223–238.
15. Manolopoulou, I., Chan, C., West, M. (2010), “Selection Sampling From Large Data Sets for Targeted Inference in Mixture Modeling” (with discussion), Bayesian Analysis, 5, 429–450.
16. Neal, R.M. (2000), Markov Chain Sampling Methods for Dirichlet Process Mixture Models, Journal of Computational and Graphical Statistics, 9, 249–265.
17. Pinto, D., (2011), Comprehensive Assessment of Array-Based Platforms and Calling Algorithms for Detection of Copy Number Variants, Nature Biotechnology, 29, 512–520.
18. Sethuraman, J. (1994), A Constructive Definition of Dirichlet Priors, Statistica Sinica, 4, 639–650.
19. Ulker, Y., Gunsel, B., Cemgil, A.T. (2011), Annealed SMC Samplers for Nonparametric Bayesian Mixture Models, IEEE Signal Processing Letters, 18, 3–6.
20. Wang, L., Dunson, D. (2011), Fast Bayesian Inference in Dirichlet Process Mixture Models, Journal of Computational and Graphical Statistics, 20, 196–216.