Confidence intervals, significance values, maximum likelihood estimates, etc. sharpened into Occam's razors

Confidence sets, p values, maximum likelihood estimates, and other results of non-Bayesian statistical methods may be adjusted to favor sampling distributions that are simple compared to others in the parametric family. The adjustments are derived from a prior likelihood function previously used to...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2020-06, Vol.49 (11), p.2703-2712
Main Author: Bickel, David R.
Format: Article
Language:English
Subjects:
Algorithmic probability
Bayesian analysis
confidence distribution
Confidence intervals
differential entropy
fiducial inference
Kolmogorov complexity
Maximum likelihood estimates
Monte Carlo simulation
probability matching prior distribution
Razors
Statistical analysis
Statistical methods
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Summary:Confidence sets, p values, maximum likelihood estimates, and other results of non-Bayesian statistical methods may be adjusted to favor sampling distributions that are simple compared to others in the parametric family. The adjustments are derived from a prior likelihood function previously used to adjust posterior distributions.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2019.1580739