Adaptive Bayesian inference on the mean of an infinite-dimensional normal distribution

From MaRDI portal
Publication:1429316

DOI10.1214/aos/1051027880zbMath1039.62039OpenAlexW2064676839MaRDI QIDQ1429316

Subhashis Ghosal, Eduard Belitser

Publication date: 18 May 2004

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1051027880



Related Items

Bayes procedures for adaptive inference in inverse problems for the white noise model, Convergence rates for posterior distributions and adaptive estimation, Bayesian change point detection for functional data, Designing truncated priors for direct and inverse Bayesian problems, Convergence rates for Bayesian density estimation of infinite-dimensional exponential families, Adaptive Bayesian Procedures Using Random Series Priors, Adaptive rates of contraction of posterior distributions in Bayesian wavelet regression, On adaptive posterior concentration rates, Adaptive nonparametric Bayesian inference using location-scale mixture priors, Adaptive Bayesian inference in the Gaussian sequence model using exponential-variance priors, Lower bound for the oracle projection posterior convergence rate, Bayesian adaptation, Nonparametric Bayesian model selection and averaging, Adaptive variational Bayes: optimality, computation and applications, Empirical Bayes scaling of Gaussian priors in the white noise model, Lower bounds for posterior rates with Gaussian process priors, Oracle convergence rate of posterior under projection prior and Bayesian model selection, Anisotropic function estimation using multi-bandwidth Gaussian processes, High-dimensional Bayesian inference in nonparametric additive models, Bayesian clustering of functional data using local features, The interplay of Bayesian and frequentist analysis, On posterior distribution of Bayesian wavelet thresholding, REGULARIZING PRIORS FOR LINEAR INVERSE PROBLEMS, Posterior contraction in sparse Bayesian factor models for massive covariance matrices, Nonparametric Bayesian inference for ergodic diffusions, Posterior contraction for empirical Bayesian approach to inverse problems under non-diagonal assumption, Adaptive filtering of a random signal in Gaussian white noise, Rates of contraction of posterior distributions based on \(p\)-exponential priors, On the posterior pointwise convergence rate of a Gaussian signal under a conjugate prior, Oracle posterior contraction rates under hierarchical priors, Empirical Bayesian test of the smoothness, Construction of credible intervals for nonlinear regression models with unknown error distributions, Optimal Bayesian smoothing of functional observations over a large graph, Rates of contraction with respect to \(L_2\)-distance for Bayesian nonparametric regression, Bayesian Optimal Adaptive Estimation Using a Sieve Prior, Consistency of Posterior Distributions for Heteroscedastic Nonparametric Regression Models, Bayesian regression with nonparametric heteroskedasticity



Cites Work