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cff-version: 1.2.0
message: 'To cite package "argminCS" in publications use:'
type: software
license: MIT
title: 'argminCS: Argmin Inference over a Discrete Candidate Set'
version: 1.1.0
doi: 10.32614/CRAN.package.argminCS
abstract: '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".'
authors:
- family-names: Zhang
  given-names: Tianyu
- family-names: Lee
  given-names: Hao
  email: haolee@andrew.cmu.edu
- family-names: Lei
  given-names: Jing
repository: https://xu3cl4.r-universe.dev
repository-code: https://github.com/xu3cl4/argminCS
commit: 575547f7d9c4e49acd87a3021c00af75724b5ead
url: https://github.com/xu3cl4/argminCS
date-released: '2025-07-07'
contact:
- family-names: Lee
  given-names: Hao
  email: haolee@andrew.cmu.edu