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pro vyhledávání: '"Fouskakis, Dimitris"'
One of the main approaches used to construct prior distributions for objective Bayes methods is the concept of random imaginary observations. Under this setup, the expected-posterior prior (EPP) offers several advantages, among which it has a nice an
Externí odkaz:
http://arxiv.org/abs/2002.05782
Publikováno v:
Computational Statistics and Data Analysis Volume 143, March 2020, 106836
The power-expected-posterior (PEP) prior is an objective prior for Gaussian linear models, which leads to consistent model selection inference, under the M-closed scenario, and tends to favor parsimonious models. Recently, two new forms of the PEP pr
Externí odkaz:
http://arxiv.org/abs/1609.06926
The power-expected-posterior (PEP) prior provides an objective, automatic, consistent and parsimonious model selection procedure. At the same time it resolves the conceptual and computational problems due to the use of imaginary data. Namely, (i) it
Externí odkaz:
http://arxiv.org/abs/1508.00793
Publikováno v:
In Computational Statistics and Data Analysis March 2020 143
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The problem motivating the paper is the quantification of students' preferences regarding teaching/coursework quality, under certain numerical restrictions, in order to build a model for identifying, assessing and monitoring the major components of t
Externí odkaz:
http://arxiv.org/abs/1404.1710
The problem of transformation selection is thoroughly treated from a Bayesian perspective. Several families of transformations are considered with a view to achieving normality: the Box-Cox, the Modulus, the Yeo & Johnson and the Dual transformation.
Externí odkaz:
http://arxiv.org/abs/1312.3482
The Zellner's g-prior and its recent hierarchical extensions are the most popular default prior choices in the Bayesian variable selection context. These prior set-ups can be expressed power-priors with fixed set of imaginary data. In this paper, we
Externí odkaz:
http://arxiv.org/abs/1307.2449
Expected-posterior priors (EPP) have been proved to be extremely useful for testing hypothesis on the regression coefficients of normal linear models. One of the advantages of using EPPs is that impropriety of baseline priors causes no indeterminacy.
Externí odkaz:
http://arxiv.org/abs/1307.2435
Publikováno v:
Bayesian Anal. Volume 10, Number 1 (2015), 75-107
In the context of the expected-posterior prior (EPP) approach to Bayesian variable selection in linear models, we combine ideas from power-prior and unit-information-prior methodologies to simultaneously produce a minimally-informative prior and dimi
Externí odkaz:
http://arxiv.org/abs/1307.2442