survival_crps: Survival continuously ranked probability score.

In ReSurv: Machine Learning Models for Predicting Claim Counts

Survival continuously ranked probability score.

Description

Return the Survival Continuously Ranked Probability Score (SCRPS) of a ReSurv model.

Usage

survival_crps(ReSurvFit, user_data_set = NULL)

Arguments

ReSurvFit	ReSurvFit object to use for the score computation.
user_data_set	data.frame provided from the user to compute the survival CRPS, optional.

Details

The model fit uses the theoretical framework of Hiabu et al. (2023), that relies on the

Value

Survival CRPS, data.table that contains the CRPS (crps) for each observation (id).

References

Pittarello, G., Hiabu, M., & Villegas, A. M. (2023). Chain Ladder Plus: a versatile approach for claims reserving. arXiv preprint arXiv:2301.03858.

Therneau, T. M., & Lumley, T. (2015). Package ‘survival’. R Top Doc, 128(10), 28-33.

Katzman, J. L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., & Kluger, Y. (2018). DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network. BMC medical research methodology, 18(1), 1-12.

Chen, T., He, T., Benesty, M., & Khotilovich, V. (2019). Package ‘xgboost’. R version, 90, 1-66.

ReSurv documentation built on April 4, 2025, 1:39 a.m.