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Noninformative priors for the two sample normal problem

Test, 1996
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Ghosh, M., Yang, M.-Ch.
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Some Remarks on Noninformative Priors

Journal of the American Statistical Association, 1995
Abstract This article focuses primarily on a comparison between the reference priors of Berger and Bernardo and the reverse reference priors suggested by J. K. Ghosh. Sufficient conditions are given that provide agreement between the two classes of priors. Several examples are given showing the agreement or disagreement between the two.
Gauri Sankar Datta, Malay Ghosh
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Noninformative Priors and Nuisance Parameters

Journal of the American Statistical Association, 1993
Abstract We study the conflict between priors that are noninformative for a parameter of interest versus priors that are noninformative for the whole parameter. Our investigation leads us to maximize a functional that has two terms: an asymptotic approximation to a standardized expected Kullback-Leibler distance between the marginal prior and marginal ...
Bertrand Clarke, Larry Wasserman
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Noninformative priors for the nested design

Journal of Statistical Planning and Inference, 2005
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Kim, Dal Ho, Kang, Sang Gil, Lee, Woo Dong   +2 more
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Noninformative priors for inferences in exponential regression models

Biometrika, 1991
Reference priors [\textit{J. O. Berger} and \textit{J. M. Bernardo}, J. Am. Stat. Assoc. 84, No. 405, 200-207 (1989; Zbl 0682.62018)] are used to estimate the regression parameter \(\rho\) in the exponential regression model given by \[ Y_{ij}\sim N(\alpha+\beta\rho^{x+x_ ia},\sigma^ 2), \] where \(\alpha,\beta\in R\), \(0 < \rho < 1\), \(x\) and \(a\)
Ye, Keying, Berger, James O.
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Hidden Dangers of Specifying Noninformative Priors

The American Statistician, 2012
“Noninformative” priors are widely used in Bayesian inference. Diffuse priors are often placed on parameters that are components of some function of interest. That function may, of course, have a prior distribution that is highly informative, in contrast to the joint prior placed on its arguments, resulting in unintended influence on the posterior for ...
John W. Seaman, John W. Seaman, James D. Stamey   +2 more
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A note on noninformative priors for Weibull distributions

Journal of Statistical Planning and Inference, 1997
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Noninformative priors for the normal variance ratio

Statistical Papers, 2007
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Kim, D. H., Kang, S. G., Lee, W. D.
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Multiresponse parameter estimation with a new and noninformative prior

Biometrika, 1987
Summary: A noninformative prior distribution for the covariance matrix of a normal distribution is derived from a data-relocated likelihood function. This new prior distribution also follows from Jeffreys's rule. Resulting modifications of current formulae for multiresponse parameter estimation are summarized.
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Bayesian analysis of vector-autoregressive models with noninformative priors

Journal of Statistical Planning and Inference, 2004
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Sun, Dongchu, Ni, Shawn
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