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SUMMARY:Piecewise Deterministic Markov Processes for transdimensional samp
 ling from flexible Bayesian survival models - Luke Hardcastle (University 
 College London)
DTSTART:20241211T150000Z
DTEND:20241211T160000Z
UID:TALK223792@talks.cam.ac.uk
DESCRIPTION: Flexible survival models have seen increasing popularity for 
 the estimation of mean survival in the presence of a high degree of admini
 strative censoring where survival curves need to be extrapolated beyond fi
 nal observed event times. This increased flexibility\, however\, often int
 roduces challenging model selection problems that have limited their wider
  application. In this talk I will focus on two such models\, the polyhazar
 d model and the piecewise exponential model. We introduce new prior struct
 ures that allow for the joint inference of parameters and structural quant
 ities. Posterior sampling is achieved using bespoke MCMC schemes based on 
 Piecewise Deterministic Markov Processes that utilise and extend existing 
 methods for these samplers to target transdimensional posterior distributi
 ons. This is a joint work with Samuel Livingstone and Gianluca Baio.
LOCATION:Seminar Room 2\, Newton Institute
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