fanc: Penalized Likelihood Factor Analysis via Nonconvex Penalty

Computes the penalized maximum likelihood estimates of factor loadings and unique variances for various tuning parameters. The pathwise coordinate descent along with EM algorithm is used. This package also includes a graphical tool which outputs path diagrams, heatmaps, goodness-of-fit indices and model selection criteria for each regularization parameter (Yamamoto, M., Hirose, K. and Nagata, H., 2017 <doi:10.1007/s41237-016-0007-3>). The user can change the regularization parameter interactively with a built-in self-contained HTML viewer (no additional packages required), which is helpful to find a suitable value of regularization parameter. As a penalty, we can choose either the minimax concave penalty (Hirose, K. and Yamamoto, M., 2015 <doi:10.1007/s11222-014-9458-0>; Hirose, K. and Yamamoto, M., 2014 <doi:10.1016/j.csda.2014.05.011>) or the product-based elastic net penalty (Hirose, K. and Terada, Y., 2023 <doi:10.1007/s11336-022-09868-4>).

Getting started

Package details

AuthorKei Hirose [aut, cre] (ORCID: <https://orcid.org/0000-0001-9827-0356>), Michio Yamamoto [aut], Haruhisa Nagata [aut]
MaintainerKei Hirose <mail@keihirose.com>
LicenseGPL (>= 2)
Version2.4.0
URL https://doi.org/10.1007/s11222-014-9458-0 https://doi.org/10.1016/j.csda.2014.05.011 https://doi.org/10.1007/s41237-016-0007-3 https://doi.org/10.1007/s11336-022-09868-4 https://keihirose.com
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("fanc")

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fanc documentation built on July 26, 2026, 9:06 a.m.