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.


Reference manual

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install.packages("transGFM")

1.0.2 by Zhijing Wang, 9 months ago


https://github.com/zjwangATsu/transGFM


Report a bug at https://github.com/zjwangATsu/transGFM/issues


Browse source code at https://github.com/cran/transGFM


Authors: Zhijing Wang [aut, cre] , Peirong Xu [aut] , Hongyu Zhao [aut] , Tao Wang [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports stats

Suggests testthat, knitr, rmarkdown


See at CRAN