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fanc  

Penalized Likelihood Factor Analysis via Nonconvex Penalty
View on CRAN: Click here


Download and install fanc package within the R console
Install from CRAN:
install.packages("fanc")

Install from Github:
library("remotes")
install_github("cran/fanc")

Install by package version:
library("remotes")
install_version("fanc", "2.3.11")



Attach the package and use:
library("fanc")
Maintained by
Kei Hirose
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-05-17
Latest Update: 2024-01-14
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. The user can change the regularization parameter by manipulating scrollbars, which is helpful to find a suitable value of regularization parameter.
How to cite:
Kei Hirose (2012). fanc: Penalized Likelihood Factor Analysis via Nonconvex Penalty. R package version 2.3.11, https://cran.r-project.org/web/packages/fanc. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.17 (2012-05-17 09:55), 0.18 (2012-05-18 12:22), 1.0 (2012-05-29 08:37), 1.1 (2012-05-31 10:46), 1.7 (2013-03-17 07:54), 1.12 (2013-08-04 11:34), 1.13 (2013-08-06 17:42), 1.22 (2015-03-18 14:35), 1.23 (2015-03-27 17:18), 1.25 (2015-09-16 12:47), 2.0 (2016-11-05 00:05), 2.1 (2016-11-08 10:56), 2.2 (2016-12-13 07:57), 2.3.5 (2022-05-24 11:50), 2.3.9 (2022-11-15 01:20), 2.3.11 (2024-01-14 16:50)
Other packages that cited fanc R package
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Other R packages that fanc depends, imports, suggests or enhances
Complete documentation for fanc
Functions, R codes and Examples using the fanc R package
Some associated functions: fanc . out.fanc . plot.fanc . select.fanc . 
Some associated R codes: fanc.R . out.fanc.R . plot.fanc.R . print.fanc.R . select.fanc.R .  Full fanc package functions and examples
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