14 citations · 15 across the 7 of their papers we have counts for
5 papers · 1 filter
Response-guided knockoffs for directional FDR control in linear models
Jack Freestone, Garth Tarr, Samuel Muller +1
We consider the problem of feature selection in linear models with finite-sample control of the false discovery rate (FDR). While existing knockoff-based methods control the direct…
Robust Best Subset Selection via Fast Approximate MM-Estimation
Martin Huang, Samuel Muller, Garth Tarr
Best subset selection procedures typically rely on a squared error loss, where a small number of outlying observations may distort the entire solution path. Replacing this loss wit…
Outlier detection in state-space models using mean-shift penalisation
Rajan Shankar, Ines Wilms, Jakob Raymaekers +1
State-space models (SSMs) provide a flexible framework for modelling time series data, but their reliance on Gaussian error assumptions makes them highly sensitive to outliers. We…
Data-Adaptive Automatic Threshold Calibration for Stability Selection
Martin Huang, Samuel Muller, Garth Tarr
Stability selection has gained popularity as a method for enhancing the performance of variable selection algorithms while controlling false discovery rates. However, achieving the…
CR-Lasso: Robust cellwise regularized sparse regression
Peng Su, Garth Tarr, Samuel Muller +1
Cellwise contamination remains a challenging problem for data scientists, particularly in research fields that require the selection of sparse features. Traditional robust methods…