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We explain how effective automatic probability density function estimates can be constructed using contemporary Bayesian inference engines such as those based on no-U-turn sampling and expectation propagation. Extensive simulation studies demonstrate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______363::32585589f34d2a726724229545eee169
https://hdl.handle.net/10453/166309
https://hdl.handle.net/10453/166309
Autor:
Hall P; School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia., Johnstone IM; Department of Statistics, Stanford University, Stanford, CA., Ormerod JT; School of Mathematics and Statistics, University of Sydney, Sydney, Australia., Wand MP; School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, Australia., Yu JCF; School of Mathematical and Physical Sciences, University of Technology Sydney, Ultimo, Australia.
Publikováno v:
Journal of the American Statistical Association [J Am Stat Assoc] 2020; Vol. 115 (532), pp. 1902-1916. Date of Electronic Publication: 2019 Oct 16.
