Consistent and conservative model selection with the adaptive Lasso in stationary and nonstationary autoregressions by Kock, A

Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models by Kock, A

Oracle inequalities for high dimensional vector autoregressions by Kock, A, Callot, L

Asymptotically honest confidence regions for high dimensional parameters by the desparsified conservative Lasso by Caner, M, Kock, A

Power in high-dimensional testing problems by Kock, A, Preinerstorfer, D

Oracle inequalities for convex loss functions with nonlinear targets by Caner, M, Kock, A

Inference in partially identified models with many moment inequalities using Lasso by Bugni, F, Caner, M, Bredahl Kock, A, Lahiri, S

Sharp threshold detection based on sup-norm error rates in high-dimensional models by Callot, L, Caner, M, Kock, A, Riquelme, J

The WIO regional benthic imagery workshop: lessons from past IIOE-2 expeditions by Haupt, T, Ceasar, J, Stefanoudis, PV, von der Meden, C, Payne, R, Adams, L, Anders, D, Bernard, A, Coetzer, W, Florence, W, Janson, L, Johnson, A, Juby, R, Kock, A, Langenkämper, D, Nadjim, A, Parker, D, Samaai, T, Snyders, L, Upfold, L, van der Heever, G, Williams, L