transGFM: Transfer Learning for Generalized Factor Models

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.

Version:	1.0.1
Depends:	R (≥ 3.5.0)
Imports:	stats
Suggests:	testthat (≥ 3.0.0), knitr, rmarkdown
Published:	2025-11-13
DOI:	10.32614/CRAN.package.transGFM (may not be active yet)
Author:	Zhijing Wang [aut, cre]
Maintainer:	Zhijing Wang <wangzhijing at sjtu.edu.cn>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	transGFM results

Documentation:

Reference manual:

transGFM.html , transGFM.pdf

Downloads:

Package source:	transGFM_1.0.1.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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