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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 2 months ago 932 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_3.conda  1 year and 2 months ago 982 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_2.conda  2 years and 3 months ago 1468 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r43hc72bb7e_2.conda  2 years and 3 months ago 1431 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r42hc72bb7e_1.tar.bz2  2 years and 11 months ago 1831 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_1.tar.bz2  2 years and 11 months ago 1803 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r40hc72bb7e_0.tar.bz2  3 years and 3 months ago 2210 main
conda 1.6 MB | noarch/r-esabcv-1.2.1.1-r41hc72bb7e_0.tar.bz2  3 years and 3 months ago 2202 main

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