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Noninformative priors for prediction based on group models
AIP Conference Proceedings, 2004Several 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
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Bayesian population estimation for small sample capture-recapture data using noninformative priors
Journal of Statistical Planning and Inference, 2007Dongchu Sun
exaly
Choice of noninformative priors for the variance components of an unbalanced one-way random model
Communications in Statistics - Theory and Methods, 1995Jean-François Angers
exaly
Bayesian analysis for the Shannon entropy of the Lomax distribution using noninformative priors
Journal of Statistical Computation and SimulationMohammed K Shakhatreh, Daojiang He
exaly
Noninformative priors for the quantile of lognormal distribution
Journal of the Korean Data And Information Science Societyopenaire +1 more source

