832 citations · 3k across the 34 of their papers we have counts for
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Confidence regions for high-dimensional generalized linear models under sparsity
Jana Janková, Sara van de Geer
We study asymptotically normal estimation and confidence regions for low-dimensional parameters in high-dimensional sparse models. Our approach is based on the -penalized M…
High-dimensional inference in misspecified linear models
Peter Bühlmann, Sara van de Geer
We consider high-dimensional inference when the assumed linear model is misspecified. We describe some correct interpretations and corresponding sufficient assumptions for valid as…
Correlated variables in regression: clustering and sparse estimation
Peter Bühlmann, Philipp Rütimann, Sara van de Geer +1
We consider estimation in a high-dimensional linear model with strongly correlated variables. We propose to cluster the variables first and do subsequent sparse estimation such as…
L1-Penalization for Mixture Regression Models
Nicolas Städler, Peter Bühlmann, Sara van de Geer
We consider a finite mixture of regressions (FMR) model for high-dimensional inhomogeneous data where the number of covariates may be much larger than sample size. We propose an l1…
Estimation for High-Dimensional Linear Mixed-Effects Models Using -Penalization
Jürg Schelldorfer, Peter Bühlmann, Sara van de Geer
We propose an -penalized estimation procedure for high-dimensional linear mixed-effects models. The models are useful whenever there is a grouping structure among high-dime…