Package: GAGAs
Type: Package
Title: Global Adaptive Generative Adjustment Algorithm for Generalized
        Linear Models
Version: 0.6.2
Language: en-US
Authors@R: c(
      person("Bin", "Wang", role=c("aut", "cre"), email="eatingbeen@hotmail.com"),
      person("Xiaofei", "Wang", role=c("ctb")),
      person("Jianhua", "Guo", role=c("ths"))
      )
Description: Fits linear regression, logistic and multinomial
        regression models, Poisson regression, Cox model via Global
        Adaptive Generative Adjustment Algorithm. For more detailed
        information, see Bin Wang, Xiaofei Wang and Jianhua Guo (2022)
        <arXiv:1911.00658>. This paper provides the theoretical
        properties of Gaga linear model when the load matrix is
        orthogonal. Further study is going on for the nonorthogonal
        cases and generalized linear models. These works are in part
        supported by the National Natural Foundation of China
        (No.12171076).
License: GPL-2
URL: https://arxiv.org/abs/1911.00658
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: Rcpp (>= 1.0.9), survival, utils
Suggests: mvtnorm
SystemRequirements: C++17
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 7.2.3
Maintainer: Bin Wang <eatingbeen@hotmail.com>
NeedsCompilation: yes
Packaged: 2026-10-10 17:57:20 UTC; root
Author: Bin Wang [aut, cre], Xiaofei Wang [ctb], Jianhua Guo [ths]
Repository: https://cran.r-universe.dev
Date/Publication: 2024-01-24 02:40:50 UTC
RemoteUrl: https://github.com/cran/GAGAs
RemoteRef: HEAD
RemoteSha: 02b3295fee662b15d9b87968e5da382d774724de