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MODERN SCIENCE AND THE BAYESIAN-FREQUENTIST CONTROVERSY
BAYESIAN-FREQUENTIST CONTROVERSY MODERN SCIENCE
2015/8/20
The 250-year debate between Bayesians and frequentists is unusual among philsophical arguments in actually having important practical consequences. Whenever
noisy data is a major concern, scientists ...
In the absence of relevant prior experience, popular Bayesian estimation techniques usually
begin with some form of \uninformative" prior distribution intended to have minimal inferential
in
uence....
A note on Bayesian credible sets in restricted parameter space problems and lower bounds for frequentist coverage
Bayesian methods Credible sets Frequentist coverage probability Lower bound Restricted Parameter Spending function
2012/9/17
For estimating a lower bounded parametric function in the framework of Marchand and Strawderman(2006), we provide “through” a unified approach a class of Bayesian confidence intervals with credibility...
Comments on "Confidence distribution, the frequentist distribution estimator of a parameter --- a review" by Min-ge Xie and Kesar Singh
the frequentist distribution estimator parameter Min-ge Xie Kesar Singh Statistics Theory
2012/6/29
This note is a discussion of the paper "Confidence distribution" by Min-ge Xie and Kesar Singh, to appear in the International Statistical Review.
Blending Bayesian and frequentist methods according to the precision of prior information with an application to hypothesis testing
blended inference confidence distribution confidence posterior
2011/7/19
The following zero-sum game between nature and a statistician blends Bayesian methods with frequentist methods such as p-values and confidence intervals. Nature chooses a posterior distribution consis...
Blending Bayesian and frequentist methods according to the precision of prior information with an application to hypothesis testing
blended inference confidence distribution confidence posterior hybrid inference maximum entropy
2011/9/30
Abstract: The following zero-sum game between nature and a statistician blends Bayesian methods with frequentist methods such as p-values and confidence intervals. Nature chooses a posterior distribut...
Frequentist Analysis of the Parameter Space of Minimal Supergravity
Frequentist Analysis Parameter Space Minimal Supergravity
2011/1/6
We make a frequentist analysis of the parameter space of minimal supergravity (mSUGRA), in which, as well as the gaugino and scalar soft supersymmetry-breaking parameters being universal.
Regularization in regression: comparing Bayesian and frequentist methods in a poorly informative situation
Regularization regression comparing Bayesian frequentist methods
2010/10/14
We propose a global noninformative approach for Bayesian variable selection that builds on Zellner's g-priors and is similar to Liang et al. (2008). Our proposal does not require any kind of calibrati...
Frequentist Bayes is Objective(Comment on Articles by Berger and by Goldstein)
coverage frequency probability objective Bayesian inference
2009/9/21
In this comment, I argue that Bayes procedures with good frequentist
properties are objective. I introduce the idea with a short play, followed by some
commentary.
On the Bayesian Approach for Frequentist Computations
the Bayesian Approach Frequentist Computations
2009/9/18
On the Bayesian Approach for Frequentist Computations。
On the frequentist coverage of Bayesian credible intervals for lower bounded means
Bayesian credible sets restricted parameter space frequentist coverage probability logconcavity
2009/9/16
For estimating a lower bounded location or mean parameter for a symmetric and logconcave density, we investigate the frequentist performance of the $100(1-alpha)%$ Bayesian HPD credible set associated...
A frequentist explanation of some universals of reflexive marking
frequentist explanation reflexive marking
2009/8/4
This paper identifies a number of empirically observable universals of reflexive marking that
concern the existence of a special reflexive pronoun and the length of the marker that is used
in refl...
On the frequentist and Bayesian approaches to hypothesis testing
Bayes factor consistency intrinsic priors loss function model posterior probability pvalues
2009/2/23
Hypothesis testing is a model selection problem for which the solution proposed by the two main
statistical streams of thought, frequentists and Bayesians, substantially differ. One may think that th...