Survival continuously ranked probability score.

Source: R/survival_crpsReSurvFit.R

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

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.

Value

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

Details

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

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.