GAGAs: Global Adaptive Generative Adjustment Algorithm for Generalized Linear Models

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) <doi:10.48550/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).

Version:	0.6.2
Depends:	R (≥ 3.6.0)
Imports:	Rcpp (≥ 1.0.9), survival, utils
LinkingTo:	Rcpp, RcppEigen
Suggests:	mvtnorm
Published:	2024-01-23
DOI:	10.32614/CRAN.package.GAGAs
Author:	Bin Wang [aut, cre], Xiaofei Wang [ctb], Jianhua Guo [ths]
Maintainer:	Bin Wang <eatingbeen at hotmail.com>
License:	GPL-2
URL:	https://arxiv.org/abs/1911.00658
NeedsCompilation:	yes
SystemRequirements:	C++17
Language:	en-US
Materials:	README NEWS
CRAN checks:	GAGAs results

Documentation:

Reference manual:

GAGAs.pdf

Downloads:

Package source:	GAGAs_0.6.2.tar.gz
Windows binaries:	r-devel: GAGAs_0.6.2.zip, r-release: GAGAs_0.6.2.zip, r-oldrel: GAGAs_0.6.2.zip
macOS binaries:	r-release (arm64): GAGAs_0.6.2.tgz, r-oldrel (arm64): GAGAs_0.6.2.tgz, r-release (x86_64): GAGAs_0.6.2.tgz, r-oldrel (x86_64): GAGAs_0.6.2.tgz
Old sources:	GAGAs archive

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