Print Email Facebook Twitter Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains Title Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains Author Bierkens, G.N.J.C. (TU Delft Statistics) Bouchard-Côté, Alexandre (University of British Columbia) Doucet, Arnaud (University of Oxford) Duncan, Andrew B. (University of Sussex) Fearnhead, Paul (University of Lancaster) Lienart, Thibaut (University of Oxford) Roberts, Gareth (University of Warwick) Vollmer, Sebastian J. (University of Warwick) Date 2018 Abstract 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. Subject Bayesian statisticsLogistic regressionMCMCPiecewise deterministic Markov processes To reference this document use: http://resolver.tudelft.nl/uuid:500507b7-b9f2-41a9-816d-2f324ba9fb50 DOI https://doi.org/10.1016/j.spl.2018.02.021 Embargo date 2020-05-25 ISSN 0167-7152 Source Statistics & Probability Letters, 136, 148-154 Bibliographical note Accepted author manuscript Part of collection Institutional Repository Document type journal article Rights © 2018 G.N.J.C. Bierkens, Alexandre Bouchard-Côté, Arnaud Doucet, Andrew B. Duncan, Paul Fearnhead, Thibaut Lienart, Gareth Roberts, Sebastian J. Vollmer Files PDF manuscript.pdf 680.14 KB Close viewer /islandora/object/uuid:500507b7-b9f2-41a9-816d-2f324ba9fb50/datastream/OBJ/view