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fastglm  

Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'
View on CRAN: Click here


Download and install fastglm package within the R console
Install from CRAN:
install.packages("fastglm")

Install from Github:
library("remotes")
install_github("cran/fastglm")

Install by package version:
library("remotes")
install_version("fastglm", "0.0.4")



Attach the package and use:
library("fastglm")
Maintained by
Jared Huling
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-03-08
Latest Update: 2022-05-23
Description:
Fits generalized linear models efficiently using 'RcppEigen'. The iteratively reweighted least squares implementation utilizes the step-halving approach of Marschner (2011) to help safeguard against convergence issues.
How to cite:
Jared Huling (2019). fastglm: Fast and Stable Fitting of Generalized Linear Models using 'RcppEigen'. R package version 0.0.4, https://cran.r-project.org/web/packages/fastglm. Accessed 05 Jun. 2026.
Previous versions and publish date:
0.0.1 (2019-03-08 16:42), 0.0.2 (2022-04-24 17:40), 0.0.3 (2022-05-23 18:50), 0.0.4 (2025-12-16 14:40)
Other packages that cited fastglm R package
View fastglm citation profile
Other R packages that fastglm depends, imports, suggests or enhances
Complete documentation for fastglm
Functions, R codes and Examples using the fastglm R package
Some associated functions: deviance . extract-methods . family . fastglm . fastglmPure . logLik . predict.fastglm . print . residuals . summary . 
Some associated R codes: RcppExports.R . bigmemory_methods.R . fastglm.R . fit_glm.R . glm_methods.R .  Full fastglm package functions and examples
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