Package: PAGE
Type: Package
Title: Predictor-Assisted Graphical Models under Error-in-Variables
Version: 0.4.0
Authors@R: c(
    person("Wan-Yi", "Chang", role=c("aut", "cre"), email="jessica306a@gmail.com"),
    person("Li-Pang", "Chen", role=c("aut"), email="lchen723@nccu.edu.tw")
    )
Description: We consider the network structure detection for variables Y with auxiliary variables X accommodated, which are possibly subject to measurement error. The following three functions are designed to address various structures by different methods : one is NP_Graph() that is used for handling the nonlinear relationship between the responses and the covariates,  another is Joint_Gaussian() that is used for correction in linear regression models via the Gaussian maximum likelihood, and the other Cond_Gaussian() is for linear regression models via conditional likelihood function.
License: GPL-3
Encoding: UTF-8
Imports: glasso, lars, network, GGally, caret, randomForest, metrica,
        MASS, stats, RSQLite
Suggests: sna
RoxygenNote: 7.3.2
Author: Wan-Yi Chang [aut, cre],
  Li-Pang Chen [aut]
Maintainer: Wan-Yi Chang <jessica306a@gmail.com>
NeedsCompilation: yes
Packaged: 2025-08-07 12:22:06 UTC; user
Repository: CRAN
Date/Publication: 2025-08-19 13:20:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 13:48:29 UTC; unix
Archs: PAGE.so.dSYM
