esaBcv: Estimate Number of Latent Factors and Factor Matrix for Factor Analysis

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 (<doi:10.48550/arXiv.1503.03515>).

Depends: R (≥ 3.0.2)
Imports: corpcor, svd
Suggests: MASS
Published: 2022-06-30
Author: Art B. Owen [aut], Jingshu Wang [aut, cre]
Maintainer: Jingshu Wang <wangjingshususan at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: Psychometrics
CRAN checks: esaBcv results


Reference manual: esaBcv.pdf


Package source: esaBcv_1.2.1.1.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): esaBcv_1.2.1.1.tgz, r-release (arm64): esaBcv_1.2.1.1.tgz, r-oldrel (arm64): esaBcv_1.2.1.1.tgz, r-prerel (x86_64): esaBcv_1.2.1.1.tgz, r-release (x86_64): esaBcv_1.2.1.1.tgz
Old sources: esaBcv archive

Reverse dependencies:

Reverse imports: cate


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