Package: PIE
Type: Package
Title: A Partially Interpretable Model with Black-Box Refinement
Version: 1.0.0
Date: 2025-01-20
Authors@R: c(person(given = "Tong",
               family = "Wang",
               role = c("aut")),
        person(given = "Jingyi",
               family = "Yang",
               role = c("aut", "cre"),
	       email = "jy4057@stern.nyu.edu"),
        person(given = "Yunyi",
               family = "Li",
               role = "aut"),
        person(given = "Boxiang",
               family = "Wang",
               role = "aut"))
Description: Implements a novel predictive model, Partially Interpretable Estimators (PIE), which jointly trains an interpretable model and a black-box model to achieve high predictive performance as well as partial model. See the paper, Wang, Yang, Li, and Wang (2021) <doi:10.48550/arXiv.2105.02410>.
Depends: R (>= 3.5.0), gglasso, xgboost
Imports: splines, stats
Encoding: UTF-8
License: GPL-2
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
Repository: CRAN
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-01-23 07:25:10 UTC; MissTiny
Author: Tong Wang [aut],
  Jingyi Yang [aut, cre],
  Yunyi Li [aut],
  Boxiang Wang [aut]
Maintainer: Jingyi Yang <jy4057@stern.nyu.edu>
Date/Publication: 2025-01-27 18:30:09 UTC
Built: R 4.6.0; ; 2026-04-27 11:35:46 UTC; unix
