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Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. (English) Zbl 1463.62215

Summary: Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live on a restricted domain.

MSC:

62J12 Generalized linear models (logistic models)
62M05 Markov processes: estimation; hidden Markov models
62F15 Bayesian inference
65C05 Monte Carlo methods

Software:

tmg; Fahrmeir
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References:

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