R-universe - penny4nonsense (Jason Parker)

factorselect - Eigenvalue-Based Estimation of the Number of Factors in Approximate Factor Models

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>.

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4.00 score 1 stars 410 downloads

depthR - Multivariate Depth Functions for General Dimension

Efficient computation of multivariate statistical depth functions in arbitrary dimension d. Implements Mahalanobis depth, Tukey (halfspace) depth, Liu simplicial depth (via adaptive Monte Carlo), projection depth, and spatial depth. Provides depth-based medians, central regions, outlier detection, and depth-depth plots. 'C++' backends via 'Rcpp' and 'RcppEigen' ensure performance at large n and d. References: Liu (1990) <doi:10.1214/aos/1176347507>, Zuo and Serfling (2000) <doi:10.1214/aos/1016218226>, Vardi and Zhang (2000) <doi:10.1073/pnas.97.4.1423>.

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cppopenmp

3.40 score