Bayesian Analysis of Failure Time Data Using P-Splines by Matthias Kaeding

By Matthias Kaeding

Matthias Kaeding discusses Bayesian tools for examining discrete and non-stop failure instances the place the influence of time and/or covariates is modeled through P-splines and extra simple functionality expansions, permitting the alternative of linear results by means of extra normal capabilities. The MCMC technique for those versions is gifted in a unified framework and utilized on information units. between others, present algorithms for the grouped Cox and the piecewise exponential version less than period censoring are mixed with an information augmentation step for the functions. the writer exhibits that the ensuing Gibbs sampler works good for the grouped Cox and is in simple terms sufficient for the piecewise exponential model.

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