# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "RGS" in publications use:'
type: software
license: MIT
title: 'RGS: Recursive Gradient Scanning Algorithm'
version: '1.0'
doi: 10.32614/CRAN.package.RGS
abstract: Provides a recursive gradient scanning algorithm for discretizing continuous
  variables in Logistic and Cox regression models. This algorithm is especially effective
  in identifying optimal cut-points for variables with U-shaped relationships to 'lnOR'
  (the natural logarithm of the odds ratio) or 'lnHR' (the natural logarithm of the
  hazard ratio), thereby enhancing model fit, interpretability, and predictive power.
  By iteratively scanning and calculating gradient changes, the method accurately
  pinpoints critical cut-points within nonlinear relationships, transforming continuous
  variables into categorical ones. This approach improves risk classification and
  regression analysis performance, increasing interpretability and practical relevance
  in clinical and risk management settings.
authors:
- family-names: Yang
  given-names: Shuo
  email: yangsh223@mail2.sysu.edu.cn
- family-names: Fei
  given-names: Yi
  email: feiy6@mail2.sysu.edu.cn
repository: https://shuo-yang-sysu.r-universe.dev
commit: 0648ccf3f813990faa60f12c7b7f3da7fd34df5f
date-released: '2024-12-19'
contact:
- family-names: Yang
  given-names: Shuo
  email: yangsh223@mail2.sysu.edu.cn