Nonparametric Bayesian estimation of a bivariate density with interval censored data

Mixture 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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Year of publication:	2008
Authors:	Yang, Mingan ; Hanson, Timothy ; Christensen, Ronald
Published in:	Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 52.2008, 12, p. 5202-5214
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005130939