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Fundamentalnaya i Prikladnaya Matematika, 2013, Volume 18, Issue 2, Pages 13–34 (Mi fpm1496)  
Bayesian model selection and the concentration of the posterior of hyperparameters

N. P. Baldina, V. G. Spokoinyabc

a Laboratory of Structural Methods of Data Analysis in Predicative Modeling, Moscow Institute of Physics and Technology, Moscow, Russia
b Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany
c Humboldt University of Berlin, Berlin, Germany
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Abstract: The present paper offers a construction of a hyperprior that can be used for Bayesian model selection. This construction is inspired by the idea of the unbiased model selection in a penalized maximum likelihood approach. The main result shows a one-sided contraction of the posterior: the posterior mass is allocated on models of lower complexity than the oracle one.
English version:
Journal of Mathematical Sciences (New York), 2014, Volume 203, Issue 6, Pages 761–776
DOI: https://doi.org/10.1007/s10958-014-2166-7
Bibliographic databases:
Document Type: Article
UDC: 519.22
Language: Russian
Citation: N. P. Baldin, V. G. Spokoiny, “Bayesian model selection and the concentration of the posterior of hyperparameters”, Fundam. Prikl. Mat., 18:2 (2013), 13–34; J. Math. Sci., 203:6 (2014), 761–776
Citation in format AMSBIB
\Bibitem{BalSpo13}
\by N.~P.~Baldin, V.~G.~Spokoiny
\paper Bayesian model selection and the concentration of the posterior of hyperparameters
\jour Fundam. Prikl. Mat.
\yr 2013
\vol 18
\issue 2
\pages 13--34
\mathnet{http://mi.mathnet.ru/fpm1496}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=3431782}
\transl
\jour J. Math. Sci.
\yr 2014
\vol 203
\issue 6
\pages 761--776
\crossref{https://doi.org/10.1007/s10958-014-2166-7}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-84922079335}
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    		Фундаментальная и прикладная математика
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