TY - GEN
T1 - Nonparametric Bayesian estimation based on beta prior in cure model
AU - Zhao, Xiaobing
AU - Xiao, Cuiliu
AU - Zhou, Xian
N1 - Copyright 2009 IEEE. Reprinted from Proceedings, the 3rd International Conference on Bioinformatics and Biomedical Engineering : iCBBE 2009 : June 11-16, 2009 Beijing, China. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Macquarie University’s products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
PY - 2009
Y1 - 2009
N2 - This paper is to study nonparametric Bayesian estimation for a proportional hazards model with "long-term survivors". The cumulative hazards function is modeled by a beta process, and the priors of the cure rate and coefficient of covariates can be improper distributions under the proposed model. The posterior estimators of the cure rate, the coefficient for covariates and the survival function are estimated from the cases of discrete-time, continuous-time and grouped survival data. A set of leukemia data are re-analyzed to illustrate the proposed model and statistical inference via a Markov chain Monte Carlo (MCMC) algorithm with Gibbs sampling.
AB - This paper is to study nonparametric Bayesian estimation for a proportional hazards model with "long-term survivors". The cumulative hazards function is modeled by a beta process, and the priors of the cure rate and coefficient of covariates can be improper distributions under the proposed model. The posterior estimators of the cure rate, the coefficient for covariates and the survival function are estimated from the cases of discrete-time, continuous-time and grouped survival data. A set of leukemia data are re-analyzed to illustrate the proposed model and statistical inference via a Markov chain Monte Carlo (MCMC) algorithm with Gibbs sampling.
UR - http://www.scopus.com/inward/record.url?scp=72749105623&partnerID=8YFLogxK
U2 - 10.1109/ICBBE.2009.5162437
DO - 10.1109/ICBBE.2009.5162437
M3 - Conference proceeding contribution
AN - SCOPUS:72749105623
SN - 9781424429028
SP - 1
EP - 6
BT - 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Piscataway, N.J
T2 - 3rd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2009
Y2 - 11 June 2009 through 13 June 2009
ER -