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Convergence rates of posterior distributions

2000
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Annals of Statistics
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We consider the asymptotic behavior of posterior distributions and Bayes estimators for infinite-dimensional statistical models. We give general results on the rate of convergence of the posterior measure. These are applied to several examples, including priors on finite sieves, log-spline models, Dirichlet processes and interval censoring. Therefore, we can verify (2.7) for n = P θ θ ∞ ≤ M and every ε n such that J n log 1 + J −α n ε n nε 2 n Next, we have, with vol J the volume of the J − 1

doi:10.1214/aos/1016218228
fatcat:pcqu3s22qjaspeh65mudxxsdo4