Results 181 to 190 of about 2,165 (200)

Bayesian analysis of vector-autoregressive models with noninformative priors

Journal of Statistical Planning and Inference, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sun, Dongchu, Ni, Shawn
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Adaptive Bayesian classification using noninformative Dirichlet priors

SMC 2000 Conference Proceedings. 2000 IEEE International Conference on Systems, Man and Cybernetics. 'Cybernetics Evolving to Systems, Humans, Organizations, and their Complex Interactions' (Cat. No.00CH37166), 2002
A model is developed to illustrate the effect that adapting correctly labeled training data with possibly incorrectly labeled data has on classification performance. The model is based on a previously developed model for mislabeled training data that uses the uniform Dirichlet distribution as a noninformative prior on the symbol probabilities of each ...
Robert S. Lynch Jr., Peter K. Willett
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Noninformative priors for the generalized half-normal distribution

Journal of the Korean Statistical Society, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kang, Sang Gil, Lee, Keunbaik, Lee, Woo Dong   +2 more
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Noninformative priors for one parameter of many

Biometrika, 1989
Summary: We consider the problem of constructing a prior that is `noninformative' for a single parameter in the presence of nuisance parameters. Our approach is to require that the resulting marginal posterior intervals have accurate frequentist coverage. \textit{C. M. Stein} [Sequential methods in statistics, Banach Cent. Publ.
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Noninformative Prior Weights for Dirichlet PDFs

2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2022
Audun Jøsang, Jin-Hee Cho, Feng Chen 0001   +2 more
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Bayesian Credibility With A Noninformative Prior

1986
A full Bayesian approach to the basic credibility problem is introduced. A solution is obtained for the balanced case and the results are compared to those obtained by empirical Bayes methods. The unbalanced case is also examined, resulting in a pseudo-estimator for the between variance.
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Murphy’s Law and Noninformative Priors

1992
In this conversation, a stockbroker offers a client some investment opportunity. But the client has very strong priors against the deal paying off. Hence, even though he has not heard anything specific about the investment, the client knows that he will probably discount the investment opportunity and find it unsatisfactory.
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On Bayesian Inference for Proportional Hazards Models Using Noninformative Priors

Lifetime Data Analysis, 2000
In this article, we investigate the properties of the posterior distribution under the uniform improper prior for two commonly used proportional hazards models; the Weibull regression model and the extreme value regression model. We allow the observations to be right censored.
Kim, Seong W., Ibrahim, Joseph G.
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Noninformative Priors for the Bivariate Fieller-Creasy Problem

Statistics & Risk Modeling, 2001
Summary: Consider two normal distributions \({\mathcal N}(\mu, \Sigma)\) and \({\mathcal N}(\theta\mu,\Sigma)\). The parameter \(\theta\) is referred to as the magnitudinal effect by \textit{I. Guttman}, \textit{U. Menzefricke} and \textit{D. Tyler} [Ann. Stat. 14, 1555-1571 (1986; Zbl 0617.62033)].
Rousseau, Judith, Ghosh, M., Kim, D.
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Noninformative Priors and Bayesian Testing for the AR(1) Model

Econometric Theory, 1994
Various approaches to the development of a noninformative prior for the AR(1) model are considered and compared. Particular attention is given to thereference priorapproach, which seems to work well for the stationary case but encounters difficulties in the explosive case.
James O. Berger, Ruo-Yong Yang
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