We propose a new Bayesian strategy for adaptation to smoothness in
nonpa...
We establish a general Bernstein–von Mises theorem for approximately lin...
Piecewise constant priors are routinely used in the Bayesian Cox proport...
We consider statistical inference in the density estimation model using ...
This work investigates multiple testing from the point of view of minima...
In the sparse sequence model, we consider a popular Bayesian multiple te...
Models with dimension more than the available sample size are now common...
Given a nonparametric Hidden Markov Model (HMM) with two states, the que...
We consider Bayesian nonparametric inference in the right-censoring surv...
In the density estimation model, the question of adaptive inference usin...
This paper affords new insights about Bayesian CART in the context of
st...
This paper explores a connection between empirical Bayes posterior
distr...
In the sparse normal means model, coverage of adaptive Bayesian posterio...
In the sparse normal means model, convergence of the Bayesian posterior
...