https://lasaibarrenada.r-universe.devRecent package updates in lasaibarrenadaR-universehttps://github.com/lasaibarrenada.pnghttps://lasaibarrenada.r-universe.devWed, 09 Sep 2026 12:39:27 GMTlasai.barrenadataleb@kuleuven.be (Lasai Barreñada)Performs exhaustive or groupwise (backward elimination) variable selection for binary outcome prediction models using cross-validated Net Benefit as the optimization criterion. It supports predictor costs, restricted cubic splines, interaction terms, permutation importance, and parallel computation. It includes visualizations for model comparison and variable importance. References include Vickers AJ & Elkin EB (2006) <doi:10.1177/0272989X06295361>, Van Calster B et al. (2018) <doi:10.1016/j.eururo.2018.08.038>, Vickers AJ et al. (2019) <doi:10.1186/s41512-019-0064-7>, and Baker SG et al. (2012) <doi:10.1515/1557-4679.1395>.https://github.com/r-universe/lasaibarrenada/actions/runs/37920735701Wed, 09 Sep 2026 12:39:27 GMTNBvarsel0.1.1successhttps://lasaibarrenada.r-universe.devhttps://github.com/lasaibarrenada/nb_varselnb-varsel-tutorial.qmdnb-varsel-tutorial.htmlVariable Selection via Net Benefit with NBvarsel2026-03-26 07:07:392026-05-17 13:04:23