Asymptotic normality, concentration, and coverage of generalized posteriors

22 July 2019

Papers citing "Asymptotic normality, concentration, and coverage of generalized posteriors"

15 / 15 papers shown

Title
A detailed treatment of Doob's theorem Jeffrey W. Miller 46 28 0 09 Jan 2018
Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution Lampros Bouranis Nial Friel Florian Maire 34 25 0 04 Oct 2015
Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields Julien Stoehr Nial Friel 33 11 0 06 Feb 2015
Finite Sample Bernstein -- von Mises Theorem for Semiparametric Problems Maxim Panov V. Spokoiny 80 44 0 29 Oct 2013
On the Bayes-optimality of F-measure maximizers Willem Waegeman Krzysztof Dembczyñski Arkadiusz Jachnik Weiwei Cheng Eyke Hullermeier 361 105 0 17 Oct 2013
Inconsistency of Pitman-Yor process mixtures for the number of components Jeffrey W. Miller M. Harrison 60 101 0 30 Aug 2013
A General Framework for Updating Belief Distributions Pier Giovanni Bissiri Chris Holmes S. Walker 131 472 0 27 Jun 2013
A Bernstein-von Mises theorem for smooth functionals in semiparametric models I. Castillo Judith Rousseau 80 117 0 20 May 2013
The Bernstein-von Mises theorem and nonregular models N. Bochkina P. Green 66 32 0 14 Nov 2012
Nonparametric Bernstein-von Mises theorems in Gaussian white noise I. Castillo Richard Nickl 93 147 0 19 Aug 2012
Bayesian inference for Gibbs random fields using composite likelihoods Nial Friel AI4CE 49 14 0 24 Jul 2012
Asymptotics for minimisers of convex processes N. Hjort D. Pollard 60 231 0 19 Jul 2011
The semiparametric Bernstein-von Mises theorem Peter J. Bickel B. Kleijn 97 125 0 01 Jul 2010
Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes M. Ribatet D. Cooley A. Davison 143 183 0 27 Nov 2009
Gibbs posterior for variable selection in high-dimensional classification and data mining Wenxin Jiang M. Tanner 64 116 0 31 Oct 2008