Nonparametric Bayesian estimation of a bivariate density with interval censored data
AbstractMixture of Polya trees nonparametric estimation of a bivariate density is presented for interval censored data. Real and simulated data are analyzed and compared with nonparametric maximum likelihood (NPMLE) and Bayesian G-spline estimates. An advantage of the mixture of Polya trees approach over the NPMLE is the relative ease with which continuous bivariate density and hazard plots are obtained.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 52 (2008)
Issue (Month): 12 (August)
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Web page: http://www.elsevier.com/locate/csda
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- Hanson, Timothy E., 2006. "Inference for Mixtures of Finite Polya Tree Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1548-1565, December.
- Lo, Shaw-Hwa & Wang, Jane-Ling, 1989. "I.i.d. representations for the bivariate product limit estimators and the bootstrap versions," Journal of Multivariate Analysis, Elsevier, vol. 28(2), pages 211-226, February.
- Argiento, Raffaele & Guglielmi, Alessandra & Pievatolo, Antonio, 2010. "Bayesian density estimation and model selection using nonparametric hierarchical mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 816-832, April.
- Lambert, Philippe, 2011. "Smooth semiparametric and nonparametric Bayesian estimation of bivariate densities from bivariate histogram data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 429-445, January.
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