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drglm
View on CRAN: Click
here
Download and install drglm package within the R console
Install from CRAN:
install.packages("drglm")
Install from Github:
library("remotes")
install_github("cran/drglm")
Install by package version:
library("remotes")
install_version("drglm", "1.1")
Attach the package and use:
library("drglm")
Maintained by
Md. Mahadi Hassan Nayem
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.drglm . https://nayemmh.github.io/drglm/ . drglm results . drglm.pdf . Introduction to Package drglm . drglm_multinom . drglm_1.1.tar.gz . drglm_1.1.zip . drglm_1.1.zip . drglm_1.1.zip . drglm_1.1.tgz . drglm_1.1.tgz . drglm_1.1.tgz . drglm_1.1.tgz . drglm archive . https://CRAN.R-project.org/package=drglm .
First Published: 2024-07-12
Latest Update: 2024-07-12
Description:
To overcome the memory limitations for fitting linear (LM) and Generalized Linear Models (GLMs) to large data sets, this package implements the Divide and Recombine (D&R) strategy. It basically divides the entire large data set into suitable subsets manageable in size and then fits model to each subset. Finally, results from each subset are aggregated to obtain the final estimate. This package also supports fitting GLMs to data sets that cannot fit into memory and provides methods for fitting GLMs under linear regression, binomial regression, Poisson regression, and multinomial logistic regression settings. Respective models are fitted using different D&R strategies as described by: Xi, Lin, and Chen (2009) <doi:10.1109/TKDE.2008.186>, Xi, Lin and Chen (2006) <doi:10.1109/TKDE.2006.196>, Zuo and Li (2018) <doi:10.4236/ojs.2018.81003>, Karim, M.R., Islam, M.A. (2019) <doi:10.1007/978-981-13-9776-9>.
How to cite:
Md. Mahadi Hassan Nayem (2024). drglm: Fitting Linear and Generalized Linear Models in "Divide and Recombine" Approach to Large Data Sets. R package version 1.1, https://cran.r-project.org/web/packages/drglm. Accessed 01 May. 2025.
Previous versions and publish date:
1.0 (2024-07-12 13:40)
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