Two UBC faculty, Harlan Campbell and Paul Gustafson, wrote a paper entitled “Defining a Credible Interval Is Not Always Possible with “Point-Null” Priors: A Lesser-Known Correlate of the Jeffreys-Lindley Paradox” in Bayesian Analysis (2024, 19, Number 3, pp. 925–984), which got discussed and presented on the BA webinar yesterday. I missed the call for discussion, […]
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a resolution of the Jeffreys-Lindley paradox
April 24, 2019“…it is possible to have the best of both worlds. If one allows the significance level to decrease as the sample size gets larger (…) there will be a finite number of errors made with probability one. By allowing the critical values to diverge slowly, one may catch almost all the errors.” (p.1527) When commenting […]
the maths of Jeffreys-Lindley paradox
March 26, 2015Cristiano Villa and Stephen Walker arXived on last Friday a paper entitled On the mathematics of the Jeffreys-Lindley paradox. Following the philosophical papers of last year, by Ari Spanos, Jan Sprenger, Guillaume Rochefort-Maranda, and myself, this provides a more statistical view on the paradox. Or “paradox”… Even though I strongly disagree with the conclusion, namely […]
another view on Jeffreys-Lindley paradox
January 15, 2015I found another paper on the Jeffreys-Lindley paradox. Entitled “A Misleading Intuition and the Bayesian Blind Spot: Revisiting the Jeffreys-Lindley’s Paradox”. Written by Guillaume Rochefort-Maranda, from Université Laval, Québec. This paper starts by assuming an unbiased estimator of the parameter of interest θ and under test for the null θ=θ0. (Which makes we wonder at the […]
“an outstanding paper that covers the Jeffreys-Lindley paradox”…
December 4, 2013“This is, in this revised version, an outstanding paper that covers the Jeffreys-Lindley paradox (JLP) in exceptional depth and that unravels the philosophical differences between different schools of inference with the help of the JLP. From the analysis of this paradox, the author convincingly elaborates the principles of Bayesian and severity-based inferences, and engages in […]
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