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: 2026-06-05 09:54:36 UTC; root
Config/pak/sysreqs: make
Repository: https://jiaqihu2021.r-universe.dev
Date/Publication: 2025-12-07 02:31:01 UTC
RemoteUrl: https://github.com/cran/REFA
RemoteRef: HEAD
RemoteSha: 38bbe506c46db127040e2e51b470e864bff8e85d