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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 12 days ago 854 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_3.conda  1 year and 12 days ago 896 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_2.conda  2 years and 2 months ago 1393 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_2.conda  2 years and 2 months ago 1348 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_1.tar.bz2  2 years and 10 months ago 1749 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_1.tar.bz2  2 years and 10 months ago 1720 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r40hc72bb7e_0.tar.bz2  3 years and 1 month ago 2132 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_0.tar.bz2  3 years and 1 month ago 2128 main

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