Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Robustness against conflicting prior information in regression   Including prior information about model parameters is a fundamental step of
any Bayesian statistical analysis. It is viewed positively by some as it
allows, among others, to quantitatively incorporate expert opinion about model
parameters. It is viewed negatively by others because it sets the stage for
subjectivity in statistical analysis. Certainly, it creates problems when the
inference is skewed due to a conflict with the data collected. According to the
theory of conflict resolution (O'Hagan and Pericchi, 2012), a solution to such
problems is to diminish the impact of conflicting prior information, yielding
inference consistent with the data. This is typically achieved by using
heavy-tailed priors. We study both theoretically and numerically the efficacy
of such a solution in regression where the prior information about the
coefficients takes the form of a product of density functions with known
location and scale parameters. We study functions with regularly-varying tails
(Student distributions), log-regularly-varying tails (as introduced in
Desgagn\'e (2015)), and propose functions with slower tail decays that allow to
resolve any conflict that can happen under that regression framework,
contrarily to the two previous types of functions. The code to reproduce all
numerical experiments is available online.

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The categories of this paper are: comp-gas
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
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The categories of this paper are: eess
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: chao-dyn
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The categories of this paper are: gr-qc
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The categories of this paper are: chem-ph
0
The categories of this paper are: hep-ph
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The categories of this paper are: math-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: supr-con
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The categories of this paper are: hep-th
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The categories of this paper are: cmp-lg