Package: fanc
Type: Package
Title: Penalized Likelihood Factor Analysis via Nonconvex Penalty
Version: 2.3.13
Date: 2026-06-03
Authors@R: 
    c(person(given = "Kei",
             family = "Hirose",
             role = c("aut", "cre"),
             email = "mail@keihirose.com",
             comment = c(ORCID = "0000-0001-9827-0356")),
      person(given = "Michio",
             family = "Yamamoto",
             role = "aut",
             email = "yamamoto.michio.hus@osaka-u.ac.jp"),
      person(given = "Haruhisa",
             family = "Nagata",
             role = "aut"))
Depends: Matrix, ellipse, tcltk
Description: 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 new graphical tool which outputs path diagram, 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 by manipulating scrollbars, 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>).
License: GPL (>= 2)
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
Repository: CRAN
NeedsCompilation: yes
Packaged: 2026-06-03 11:27:10 UTC; hirosekei
Author: Kei Hirose [aut, cre] (ORCID: <https://orcid.org/0000-0001-9827-0356>),
  Michio Yamamoto [aut],
  Haruhisa Nagata [aut]
Maintainer: Kei Hirose <mail@keihirose.com>
Date/Publication: 2026-06-04 15:00:02 UTC
