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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  8 months and 11 days ago 596 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_3.conda  8 months and 11 days ago 648 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_2.conda  1 year and 9 months ago 1149 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_2.conda  1 year and 9 months ago 1115 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_1.tar.bz2  2 years and 6 months ago 1509 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_1.tar.bz2  2 years and 6 months ago 1480 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r40hc72bb7e_0.tar.bz2  2 years and 9 months ago 1899 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_0.tar.bz2  2 years and 9 months ago 1894 main

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