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Abstract Details

Activity Number: 352
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #306321
Title: A Novel Nonparametric Prior Based on Transformed Bernstein Polynomial
Author(s): Yuhui Chen*+ and Timothy Hanson
Companies: and University of South Carolina
Address: 241 S. Bull Street, Columbia, SC, 29205, United States
Keywords: Tansformed Berntein Polynomial Priors ; Density Estimation ; Accelerated Hazard Model ; Time-dependent Covariates

We propose a transformed Bernstein polynomial that is centered at standard parametric families, such as Weibull. As such, this class provides an extremely convenient way towards creating a Bayesian non-parametric prior for smooth densities, blending the merits of parametric and non-parametric methods. This prior gives very smooth densities that are amenable to standard estimation approaches; for example optimization methods in SAS or R can yield the posterior mode and asymptotic covariance matrix. This novel nonparametric prior is emplyed in the accelerated hazard model, which is further generalized to time-dependent covariates and a joint longitudinal / accelerated hazard model.

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