Smooth estimates of normal mixtures

Canadian Journal of Statistics

Volumn 28, Issue 3, 2000, Pages 551-562

  Tong, Barbara ^a   Viele, Kert ^b  

^a NOVARTIS PHARMA AG   (Switzerland)

^b UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Markov chain Monte Carlo; Predictive density

Indexed keywords

EID: 0034356155     PISSN: 03195724     EISSN: None     Source Type: Journal    
DOI: 10.2307/3315964     Document Type: Article

References (12)

1. M. Aitkin & G. Wilson (1980). Mixture models, outliers, and the EM algorithm. Technometrics, 22, 325-331.
2. N. E. Day (1969). Estimating the components of a mixture of normal distributions. Biometrika, 56, 463-474.
3. R. D. De Veaux (1989). Mixtures of linear regressions. Computational Statistics and Data Analysis, 8, 227-245.
4. W. R. Gilks, S. Richardson & D. J. Spiegelhalter (1996). Markov Chain Monte Carlo in Practice. Chapman and Hall.
5. R. J. Hathaway (1985). A constrained formulation of maximum-likelihood estimation for normal mixture distributions. The Annals of Statistics, 13, 795-800.
6. K. L. Mengersen & C. Robert (1996). Testing for mixtures: A Bayesian entropic approach. In Bayesian Statistics 5 (J. M. Bernardo, J. O. Berger, A. P. Dawid & A. F. M. Smith, eds.), Clarendon Press, pp. 255-276.
7. Richardson & Green (1997). On Bayesian analysis of mixtures with an unknown number of components (with discussion). Journal of the Royal Statistical Society Series B, 59, 731-792.
8. C. Robert (1996). Mixtures of distributions: Inference and estimation. In Markov Chain Monte Carlo in Practice (W. R. Gilks, S. Richardson and D. J. Spiegelhalter, eds.), Chapman and Hall, Chapter 24.
9. K. Roeder (1990). Density estimation with confidence sets exemplified by superclusters and voids in the galaxies. Journal of the American Statistical Association, 85, 617-624.
10. K. Roeder & L. A. Wasserman (1997). Practical Bayesian density estimation using mixtures of normals. Journal of the American Statistical Association, 92, 894-902.
11. L. J. Tierney (1994). Markov chains for exploring posterior distributions (with discussion). The Annals of Statistics, 22, 1701-1762.
12. K. Viele (2000). Posterior simulation with priors specified on functionals. Journal of Computational and Graphical Statistics, 9, 235-248.