2 citations · 4 across the 7 of their papers we have counts for
7 papers
Inferring High-Dimensional Dynamic Networks Changing with Multiple Covariates
Louis Dijkstra, Arne Godt, Ronja Foraita
High-dimensional networks play a key role in understanding complex relationships. These relationships are often dynamic in nature and can change with multiple external factors (e.g…
An Alternating Direction Method of Multipliers Algorithm for the Weighted Fused LASSO Signal Approximator
Louis Dijkstra, Moritz Hanke, Niklas Koenen +1
We present an Alternating Direction Method of Multipliers (ADMM) algorithm designed to solve the Weighted Generalized Fused LASSO Signal Approximator (wFLSA). First, we show that w…
Improving Finite Sample Performance of Causal Discovery by Exploiting Temporal Structure
Christine W Bang, Janine Witte, Ronja Foraita +1
Methods of causal discovery aim to identify causal structures in a data driven way. Existing algorithms are known to be unstable and sensitive to statistical errors, and are theref…
An Exposure Model Framework for Signal Detection based on Electronic Healthcare Data
Louis Dijkstra, Tania Schink, Ronja Foraita
Despite extensive safety assessments of drugs prior to their introduction to the market, certain adverse drug reactions (ADRs) remain undetected. The primary objective of pharmacov…
Variable selection in linear regression models: choosing the best subset is not always the best choice
Moritz Hanke, Louis Dijkstra, Ronja Foraita +1
Variable selection in linear regression settings is a much discussed problem. Best subset selection (BSS) is often considered the intuitive 'gold standard', with its use being rest…
Multiple imputation and test-wise deletion for causal discovery with incomplete cohort data
Janine Witte, Ronja Foraita, Vanessa Didelez
Causal discovery algorithms estimate causal graphs from observational data. This can provide a valuable complement to analyses focussing on the causal relation between individual t…
A practical guide to causal discovery with cohort data
Ryan M. Andrews, Ronja Foraita, Vanessa Didelez +1
In this guide, we present how to perform constraint-based causal discovery using three popular software packages: pcalg (with add-ons tpc and micd), bnlearn, and TETRAD. We focus o…