Package: REFA
Type: Package
Title: Robust Exponential Factor Analysis
Date: 2025-12-06
Version: 0.2.0
Authors@R: c(
  person(given = "Jiaqi", family = "Hu", email = "hujiaqi@mail.ustc.edu.cn", role = c("cre", "aut")),
  person(given = "Xueqin", family = "Wang", email = "wangxq20@ustc.edu.cn", role = c("aut")))
Author: Jiaqi Hu [cre, aut],
  Xueqin Wang [aut]
Maintainer: Jiaqi Hu <hujiaqi@mail.ustc.edu.cn>
Description: A robust alternative to the traditional principal component estimator is proposed within the framework of factor models, known as Robust Exponential Factor Analysis, specifically designed for the modeling of high-dimensional datasets with heavy-tailed distributions. The algorithm estimates the latent factors and the loading by minimizing the exponential squared loss function. To determine the appropriate number of factors, we propose a modified rank minimization technique, which has been shown to significantly enhance finite-sample performance. For more detail of Robust Exponential Factor Analysis, please refer to Hu et al. (2026) <doi:10.1016/j.jmva.2025.105567>.
Imports: fMultivar
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2025-12-06 17:07:33 UTC; hujiaqi
Repository: CRAN
Date/Publication: 2025-12-07 00:40:20 UTC
Built: R 4.6.0; ; 2026-04-28 09:35:32 UTC; unix
