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In Bayesian theory, calculating a posterior probability distribution is highly important but usually difficult. Therefore, some methods have been put forward to deal with such problem, among which, th...
In this paper, we investigate the asymptotic properties of nonparametric Bayesian mixtures of Betas for estimating a smooth density on [0, 1]. We consider a parametrization of Beta distributions in ...
Any unperturbed and perturbed posterior density can formally be linked by a mixture. Many divergences between the unperturbed and perturbed posterior density-global measures of inuenceof the perturb...
Coherence, Bayess Theorem and Posterior Distributions
Posterior Distributions for the Laplace Mean Arising from Ratios
We consider evaluation of proper posterior distributions obtained from improper prior distributions. Our context is estimating a bounded function  of a parameter when the loss is quadratic. If the ...
We extend the approach of Walker (2003, 2004) to the case of misspecified models. A sufficient condition for establishing rates of convergence is given based on a key identity involving martingales,...

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