5 citations · 8 across the 3 of their papers we have counts for
3 papers
math.ST2017
On overfitting and post-selection uncertainty assessments
Liang Hong, Todd A. Kuffner, Ryan Martin
In a regression context, when the relevant subset of explanatory variables is uncertain, it is common to use a data-driven model selection procedure. Classical linear model theory,…
math.ST2012★ 5 cited
On convergence rates of Bayesian predictive densities and posterior distributions
Ryan Martin, Liang Hong
Frequentist-style large-sample properties of Bayesian posterior distributions, such as consistency and convergence rates, are important considerations in nonparametric problems. In…
math.ST2012★ 3 cited
A note on Bayesian convergence rates under local prior support conditions
Ryan Martin, Liang Hong, Stephen G. Walker
Bounds on Bayesian posterior convergence rates, assuming the prior satisfies both local and global support conditions, are now readily available. In this paper we explore, in the c…