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ReSurv  

Machine Learning Models for Predicting Claim Counts
View on CRAN: Click here


Download and install ReSurv package within the R console
Install from CRAN:
install.packages("ReSurv")

Install from Github:
library("remotes")
install_github("cran/ReSurv")

Install by package version:
library("remotes")
install_version("ReSurv", "1.0.0")



Attach the package and use:
library("ReSurv")
Maintained by
Emil Hofman
[Scholar Profile | Author Map]
First Published: 2024-11-14
Latest Update: 2024-11-14
Description:
Prediction of claim counts using the feature based development factors introduced in the manuscript Hiabu M., Hofman E. and Pittarello G. (2023) <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.
How to cite:
Emil Hofman (2024). ReSurv: Machine Learning Models for Predicting Claim Counts. R package version 1.0.0, https://cran.r-project.org/web/packages/ReSurv. Accessed 01 May. 2025.
Previous versions and publish date:
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Complete documentation for ReSurv
Functions, R codes and Examples using the ReSurv R package
Full ReSurv package functions and examples
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