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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "ReSurv" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'ReSurv: Machine Learning Models for Predicting Claim Counts'
version: 1.0.0
doi: 10.32614/CRAN.package.ReSurv
abstract: Prediction of claim counts using the feature based development factors introduced
  in the manuscript Hiabu M., Hofman E. and Pittarello G. (2023) <https://doi.org/10.48550/arXiv.2312.14549>.
  Implementation of Neural Networks, Extreme Gradient Boosting, and Cox model with
  splines to optimise the partial log-likelihood of proportional hazard models.
authors:
- family-names: Hofman
  given-names: Emil
  email: emil_hofman@hotmail.dk
- family-names: Pittarello
  given-names: Gabriele
  email: gabriele.pittarello@uniroma1.it
  orcid: https://orcid.org/0000-0003-3360-5826
- family-names: Hiabu
  given-names: Munir
  email: mh@math.ku.dk
  orcid: https://orcid.org/0000-0001-5846-667X
repository: https://CRAN.R-project.org/package=ReSurv
repository-code: https://github.com/edhofman/ReSurv
url: https://github.com/edhofman/ReSurv
date-released: '2024-11-14'
contact:
- family-names: Hofman
  given-names: Emil
  email: emil_hofman@hotmail.dk