1 citations · 1 across the 3 of their papers we have counts for
3 papers
Bad estimation, good prediction: the Lasso in dense regimes
Andrea Bratsberg, Magne Thoresen, Jelle J. Goeman
For high-dimensional omics data, sparsity-inducing regularization methods such as the Lasso are widely used and often yield strong predictive performance, even in settings when the…
Conditional variable screening for ultra-high dimensional longitudinal data with time interactions
Andrea Bratsberg, Abhik Ghosh, Magne Thoresen
In recent years we have been able to gather large amounts of genomic data at a fast rate, creating situations where the number of variables greatly exceeds the number of observatio…
Exponential Consistency of M-estimators in Generalized Linear Mixed Models
Andrea M. Bratsberg, Magne Thoresen, Abhik Ghosh
Generalized linear mixed models are powerful tools for analyzing clustered data, where the unknown parameters are classically (and most commonly) estimated by the maximum likelihoo…