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Nonparametric Bayesian estimation of a bivariate density with interval censored data

  • Yang, Mingan
  • Hanson, Timothy
  • Christensen, Ronald
Registered author(s):

    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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    File URL: http://www.sciencedirect.com/science/article/B6V8V-4SBY4NY-1/2/a07ca01866474a822245ef4eac93137b
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    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 52 (2008)
    Issue (Month): 12 (August)
    Pages: 5202-5214

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    Handle: RePEc:eee:csdana:v:52:y:2008:i:12:p:5202-5214
    Contact details of provider: Web page: http://www.elsevier.com/locate/csda

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    1. Berger J. O & Guglielmi A., 2001. "Bayesian and Conditional Frequentist Testing of a Parametric Model Versus Nonparametric Alternatives," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 174-184, March.
    2. 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.
    3. 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.
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