24 citations · 28 across the 6 of their papers we have counts for
3 papers · 1 filter
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,…
Optimal hybrid block bootstrap for sample quantiles under weak dependence
Todd A. Kuffner, Stephen M. S. Lee, G. Alastair Young
We establish a general theory of optimality for block bootstrap distribution estimation for sample quantiles under a mild strong mixing assumption. In contrast to existing results,…
On the validity of the formal Edgeworth expansion for posterior densities
John E. Kolassa, Todd A. Kuffner
We consider a fundamental open problem in parametric Bayesian theory, namely the validity of the formal Edgeworth expansion of the posterior density. While the study of valid asymp…