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cff-version: 1.2.0
message: 'To cite package "srlars" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'srlars: Fast and Scalable Cellwise-Robust Ensemble'
version: 3.0.0
doi: 10.32614/CRAN.package.srlars
abstract: Functions to perform robust variable selection and regression using the
  Fast and Scalable Cellwise-Robust Ensemble (FSCRE) algorithm. The approach establishes
  a robust foundation using the Detect Deviating Cells (DDC) algorithm and robust
  correlation estimates. It then employs a competitive ensemble architecture where
  a robust Least Angle Regression (LARS) engine proposes candidate variables and cross-validation
  arbitrates their assignment. A final robust MM-estimator is applied to the selected
  predictors.
authors:
- family-names: Christidis
  given-names: Anthony
  email: anthony.christidis@stat.ubc.ca
- family-names: Cohen-Freue
  given-names: Gabriela
  email: gcohen@stat.ubc.ca
repository: https://cran.r-universe.dev
commit: 3780d7b1606f8d6fa50256f48c16b50aa07cec8c
date-released: '2026-06-12'
contact:
- family-names: Christidis
  given-names: Anthony
  email: anthony.christidis@stat.ubc.ca