Transfer learning for time-to-event modelling via Bregman divergence.
SurvBregDiv enables principled borrowing of external information when fitting Cox proportional hazards or nested case–control (NCC) models, through a unified Bregman-divergence framework that accommodates population heterogeneity between internal and external cohorts.
Using SurvBregDiv with an AI assistant?
An AI-optimized reference is published at https://um-kevinhe.github.io/SurvBregDiv/llms.txt (following the llms.txt convention). Point your AI at that URL, or paste its contents into the chat, to give the assistant a compact map of the package — decision tree, parameter reference, worked examples, and common pitfalls — without ingesting the full website.
Installation
# CRAN
install.packages("SurvBregDiv")
# Development version from GitHub
remotes::install_github("UM-KevinHe/SurvBregDiv")Requires R ≥ 4.0.
Documentation
- Tutorials and methodology: https://um-kevinhe.github.io/SurvBregDiv/
- Function reference: https://um-kevinhe.github.io/SurvBregDiv/reference/
Getting help
The package is under active development; please report issues or unexpected behavior to any of the maintainers:
- Yubo Shao — ybshao@umich.edu
- Junyi Qiu — junyiqiu@umich.edu
- Kevin He — kevinhe@umich.edu