https://xu3cl4.r-universe.devRecent package updates in xu3cl4R-universehttps://github.com/xu3cl4.pnghttps://xu3cl4.r-universe.devWed, 09 Jul 2025 02:21:52 GMThaolee@andrew.cmu.edu (Hao Lee)Provides methods to construct frequentist confidence sets with valid marginal coverage for identifying the population-level argmin or argmax based on IID data. For instance, given an n by p loss matrix—where n is the sample size and p is the number of models—the CS.argmin() method produces a discrete confidence set that contains the model with the minimal (best) expected risk with desired probability. The argmin.HT() method helps check if a specific model should be included in such a confidence set. The main implemented method is proposed by Tianyu Zhang, Hao Lee and Jing Lei (2024) "Winners with confidence: Discrete argmin inference with an application to model selection".https://github.com/r-universe/xu3cl4/actions/runs/26152027358Wed, 09 Jul 2025 02:21:52 GMTargminCS1.1.0successhttps://xu3cl4.r-universe.devhttps://github.com/xu3cl4/argmincs