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Noninformative priors for prediction based on group models

AIP Conference Proceedings, 2004
Several topics concerning noninformative priors and prediction for group models are considered. The Kullback‐Leibler divergence from the true distribution to a predictive distribution is adopted as a loss function.When a model has a group structure, the right invariant measure is often recommended as a noninformative prior. We consider group models and
openaire   +1 more source

Brief Research Report: Bayesian Versus REML Estimations With Noninformative Priors in Multilevel Single-Case Data

Journal of Experimental Education, 2020
Eunkyeng Baek   +2 more
exaly  

Choice of noninformative priors for the variance components of an unbalanced one-way random model

Communications in Statistics - Theory and Methods, 1995
Jean-François Angers
exaly  

Posterior Properties of the Nakagami-m Distribution Using Noninformative Priors and Applications in Reliability

IEEE Transactions on Reliability, 2018
Pedro L Ramos   +2 more
exaly  

Bayesian analysis for the Shannon entropy of the Lomax distribution using noninformative priors

Journal of Statistical Computation and Simulation
Mohammed K Shakhatreh, Daojiang He
exaly  

Noninformative priors for the quantile of lognormal distribution

Journal of the Korean Data And Information Science Society
openaire   +1 more source

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