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  "Title": "Eigenvalue-Based Estimation of the Number of Factors in\nApproximate Factor Models",
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  "Description": "Eigenvalue-based estimation of the number of factors in\napproximate factor models. Designed to work when either N or T\nis large, without requiring both dimensions to grow\nsimultaneously. Implements the eigenvalue ratio estimator of\nAhn and Horenstein (2013) <doi:10.3982/ECTA8968>, the\ninformation criteria of Bai and Ng (2002)\n<doi:10.1111/1468-0262.00273>, the tuned penalty of Alessi,\nBarigozzi and Capasso (2010) <doi:10.1016/j.spl.2010.08.005>,\nthe auto-covariance ratio estimator of Lam and Yao (2012)\n<doi:10.1214/12-AOS970>, and the edge distribution estimators\nof Onatski (2009) <doi:10.3982/ECTA6964> and Onatski (2010)\n<doi:10.1162/REST_a_00043>.",
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  "Date/Publication": "2026-04-22 16:45:48 UTC",
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