DESCRIPTION

Package: ReSurv
Type: Package
Title: Machine Learning Models For Predicting Claim Counts
Version: 1.0.0
Authors@R:
    c(person(given = "Emil",
             family = "Hofman",
             role = c("aut", "cre", "cph"),
             email="emil_hofman@hotmail.dk"),
      person(given = "Gabriele",
             family = "Pittarello",
             role = c("aut", "cph"),
             email = "gabriele.pittarello@uniroma1.it",
             comment = c(ORCID = "0000-0003-3360-5826")),
      person(given = "Munir",
             family = "Hiabu",
             email="mh@math.ku.dk",
             role = c("aut", "cph"),
             comment = c(ORCID = "0000-0001-5846-667X")))
Description: Prediction of claim counts using the feature based development factors introduced in the manuscript <doi: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.
URL: https://github.com/edhofman/ReSurv
BugReports: https://github.com/edhofman/ReSurv/issues
License: GPL (>= 2)
Depends: tidyverse
Imports: 
  stats,
  dplyr,
  dtplyr,
  fastDummies,
  forecast,
  data.table,
  purrr,
  tidyr,
  tibble,
  ggplot2,
  survival,
  reshape2,
  bshazard,
  SynthETIC,
  rpart,
  reticulate, 
  xgboost,
  SHAPforxgboost
SystemRequirements: Python (>= 3.8.0)
Encoding: UTF-8
LazyData: true
Suggests: 
  knitr,
  rmarkdown
VignetteBuilder: knitr, rmarkdown
RoxygenNote: 7.3.2