Results 171 to 180 of about 2,165 (200)
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Hidden Dangers of Specifying Noninformative Priors
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, James D Stamey
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Noninformative priors for the nested design
Journal of Statistical Planning and Inference, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, Dal Ho +2 more
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Noninformative priors for inferences in exponential regression models
Biometrika, 1991Reference 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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Bayesian Estimation of the Number of Species using Noninformative Priors
Biometrical Journal, 2008AbstractConsider a sample of animal abundances collected from one sampling occasion. Our focus is in estimating the number of species in a closed population. In order to conduct a noninformative Bayesian inference when modeling this data, we derive Jeffreys and reference priors from the full likelihood.
John Bunge
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A note on noninformative priors for Weibull distributions
Journal of Statistical Planning and Inference, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Developing Noninformative Priors for Parallel-Line Bioassay [PDF]
Communications for Statistical Applications and Methods, 2002 This paper revisits parallel-line bioassay problem, from a Bayesian point of view using noninformative priors such as Jeffreys' prior, reference priors, and probability matching priors. After finding the orthogonal transformation, the class of first order and second order probability matching priors are derived. Jeffreys' prior and reference priors are
YeongHwa Kim, JungEun Heo
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Constrained noninformative priors in risk assessment
Reliability Engineering and System Safety, 1996Abstract A constrained noninformative prior distribution, a generalization of the Jeffreys noninformative prior, is defined for a single unknown parameter as the distribution corresponding to the maximum entropy distribution, subject to the assumed constraint(s), in the transformed model where the unknown parameter is approximately a location ...
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Bayesian analysis for a stress-strength system under noninformative priors
Canadian Journal of Statistics, 1998AbstractNoninformative priors are used for estimating the reliability of a stress‐strength system. Several reference priors (cf. Berger and Bernardo 1989, 1992) are derived. A class of priors is found by matching the coverage probabilities of one‐sided Bayesian credible intervals with the corresponding frequentist coverage probabilities.
Dongchu Sun, , Asit P Basu
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Noninformative priors for linear combinations of the normal means
Statistical Papers, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dal Ho Kim, Sang Gil Kang, Woo Dong Lee
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Multiresponse parameter estimation with a new and noninformative prior
Biometrika, 1987Summary: 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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