Eigenvalue-Based Estimation of the Number of Factors in Approximate Factor Models R package factorselect version 0.1.3 Eigenvalue-based estimation of the number of factors in approximate factor models. Designed to work when either N or T is large, without requiring both dimensions to grow simultaneously. Implements the eigenvalue ratio estimator of Ahn and Horenstein (2013) <doi:10.3982/ECTA8968>, the information criteria of Bai and Ng (2002) <doi:10.1111/1468-0262.00273>, the tuned penalty of Alessi, Barigozzi and Capasso (2010) <doi:10.1016/j.spl.2010.08.005>, the auto-covariance ratio estimator of Lam and Yao (2012) <doi:10.1214/12-AOS970>, and the edge distribution estimators of Onatski (2009) <doi:10.3982/ECTA6964> and Onatski (2010) <doi:10.1162/REST_a_00043>. Software Suggests: RSpectra, testthat (>= 3.0.0), knitr, rmarkdown Jason Parker <jparker588@gmail.com> Comprehensive R Archive Network (CRAN) Jason Parker [aut, cre] (ORCID: <https://orcid.org/0000-0001-9227-6976>) MIT + file LICENSE (https://CRAN.R-project.org/package=factorselect/LICENSE) 2026-04-28 application/tgz https://CRAN.R-project.org/package=factorselect doi:10.32614/CRAN.package.factorselect