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stat.ME2025
Entropy Adjusted Graphical Lasso for Sparse Precision Matrix Estimation
Vahe Avagyan
The estimation of a precision matrix is a crucial problem in various research fields, particularly when working with high dimensional data. In such settings, the most common approa…
stat.ME2018
Doubly robust tests of exposure effects under high-dimensional confounding
Oliver Dukes, Vahe Avagyan, Stijn Vansteelandt
After variable selection, standard inferential procedures for regression parameters may not be uniformly valid; there is no finite-sample size at which a standard test is guarantee…
stat.ME2017★ 17 cited
Honest data-adaptive inference for the average treatment effect under model misspecification using penalised bias-reduced double-robust estimation
Vahe Avagyan, Stijn Vansteelandt
The presence of confounding by high-dimensional variables complicates estimation of the average effect of a point treatment. On the one hand, it necessitates the use of variable se…