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transGFM  

Transfer Learning for Generalized Factor Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("transGFM", "1.0.2")



Attach the package and use:
library("transGFM")
Maintained by
Zhijing Wang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-13
Latest Update: 2025-11-13
Description:
Transfer learning for generalized factor models with support for continuous, count (Poisson), and binary data types. The package provides functions for single and multiple source transfer learning, source detection to identify positive and negative transfer sources, factor decomposition using Maximum Likelihood Estimation (MLE), and information criteria ('IC1' and 'IC2') for rank selection. The methods are particularly useful for high-dimensional data analysis where auxiliary information from related source datasets can improve estimation efficiency in the target domain.
How to cite:
Zhijing Wang (2025). transGFM: Transfer Learning for Generalized Factor Models. R package version 1.0.2, https://cran.r-project.org/web/packages/transGFM. Accessed 11 Mar. 2026.
Previous versions and publish date:
1.0.1 (2025-11-13 19:40)
Other packages that cited transGFM R package
View transGFM citation profile
Other R packages that transGFM depends, imports, suggests or enhances
Complete documentation for transGFM
Functions, R codes and Examples using the transGFM R package
Full transGFM package functions and examples
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