4 papers · 1 filter
Can we have it all? Non-asymptotically valid and asymptotically exact confidence intervals for expectations and linear regressions
Alexis Derumigny, Lucas Girard, Yannick Guyonvarch
We contribute to bridging the gap between large- and finite-sample inference by studying confidence sets (CSs) that are both non-asymptotically valid and asymptotically exact unifo…
Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
Rutger van der Spek, Alexis Derumigny
Kendall's tau and conditional Kendall's tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available e…
Lower bounds for the trade-off between bias and mean absolute deviation
Alexis Derumigny, Johannes Schmidt-Hieber
In nonparametric statistics, rate-optimal estimators typically balance bias and stochastic error. The recent work on overparametrization raises the question whether rate-optimal es…
Codivergences and information matrices
Alexis Derumigny, Johannes Schmidt-Hieber
We propose a new concept of codivergence, which quantifies the similarity between two probability measures relative to a reference probability measure . In the neig…