7 papers · 1 filter
Estimation beyond Missing (Completely) at Random
Tianyi Ma, Kabir A. Verchand, Thomas B. Berrett +2
We study the effects of missingness on the estimation of population parameters. Moving beyond restrictive missing completely at random (MCAR) assumptions, we first formulate a miss…
Learning the score under shape constraints
Rebecca M. Lewis, Oliver Y. Feng, Henry W. J. Reeve +2
Score estimation has recently emerged as a key modern statistical challenge, due to its pivotal role in generative modelling via diffusion models. Moreover, it is an essential ingr…
Nonparametric inference under shape constraints: past, present and future
Richard J. Samworth
We survey the field of nonparametric inference under shape constraints, providing a historical overview and a perspective on its current state. An outlook and some open problems of…
False discovery rate control with compound p-values
Rina Foygel Barber, Richard J Samworth
In the setting of multiple testing, compound p-values generalize p-values by asking for superuniformity to hold only \emph{on average} across all true nulls. We study the propertie…
Optimal convex -estimation via score matching
Oliver Y. Feng, Yu-Chun Kao, Min Xu +1
In the context of linear regression, we construct a data-driven convex loss function with respect to which empirical risk minimisation yields optimal asymptotic variance in the dow…
High-probability minimax lower bounds
Tianyi Ma, Kabir A. Verchand, Richard J. Samworth
The minimax risk is often considered as a gold standard against which we can compare specific statistical procedures. Nevertheless, as has been observed recently in robust and heav…