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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 3 days ago 580 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_3.conda  8 months and 3 days ago 630 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_2.conda  1 year and 9 months ago 1134 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_2.conda  1 year and 9 months ago 1100 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_1.tar.bz2  2 years and 5 months ago 1492 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_1.tar.bz2  2 years and 5 months ago 1464 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r40hc72bb7e_0.tar.bz2  2 years and 9 months ago 1880 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_0.tar.bz2  2 years and 9 months ago 1876 main

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