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These functions estimate the latent factors of a given matrix, no matter it is high-dimensional or not. It tries to first estimate the number of factors using bi-cross-validation and then estimate the latent factor matrix and the noise variances. For more information about the method, see Art B. Owen and Jingshu Wang 2015 archived article on factor model (http://arxiv.org/abs/1503.03515).

copied from cf-staging / r-esabcv
Type Size Name Uploaded Downloads Labels
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r44hc72bb7e_3.conda  1 year and 18 days ago 863 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_3.conda  1 year and 18 days ago 905 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_2.conda  2 years and 2 months ago 1402 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_2.conda  2 years and 2 months ago 1356 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_1.tar.bz2  2 years and 10 months ago 1758 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_1.tar.bz2  2 years and 10 months ago 1728 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r40hc72bb7e_0.tar.bz2  3 years and 1 month ago 2141 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_0.tar.bz2  3 years and 1 month ago 2137 main

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