Abstract
A Bayesian analysis of the semi-parametric regression model of Cox (1972) is given. The cumulative hazard function is modelled as a beta process. The posterior distribution of the regression parameters and the survival function are obtained using a combination of recent Monte Carlo methods. An illustrative analysis within the context of survival time data is given.
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Laud, P.W., Damien, P., Smith, A.F.M. (1998). Bayesian Nonparametric and Covariate Analysis of Failure Time Data. In: Dey, D., Müller, P., Sinha, D. (eds) Practical Nonparametric and Semiparametric Bayesian Statistics. Lecture Notes in Statistics, vol 133. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1732-9_11
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DOI: https://doi.org/10.1007/978-1-4612-1732-9_11
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