7 papers · 1 filter
Direct and efficient estimation of bilinear forms in staggered tensor panels
Alberto Bordino, Thomas B. Berrett, Olga Klopp
We study the estimation of bilinear forms from noisy, partially observed tensor data. The signal follows a Tucker2 model, with shared unit and time factors across tensor layers and…
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…
Locally Differentially Private Two-Sample Testing
Alexander Kent, Thomas B. Berrett, Yi Yu
We consider the problem of two-sample testing under a local differential privacy constraint where a permutation procedure is used to calibrate the tests. We develop testing procedu…
Semi-supervised linear regression with missing covariates
Benedict M. Risebrow, Thomas B. Berrett
Missing values in datasets are common in applied statistics. For regression problems, theoretical work thus far has largely considered the issue of missing covariates as distinct f…
Rate Optimality and Phase Transition for User-Level Local Differential Privacy
Alexander Kent, Thomas B. Berrett, Yi Yu
Most of the literature on differential privacy considers the item-level case where each user has a single observation, but a growing field of interest is that of user-level privacy…
Efficient estimation with incomplete data via generalised ANOVA decompositions
Thomas B. Berrett
We study the semiparametric efficient estimation of a class of linear functionals in settings where a complete multivariate dataset is supplemented by additional datasets recording…