Machine Learning Models for Predicting Claim Counts


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Documentation for package ‘ReSurv’ version 1.0.0

Help Pages

data_generator Individual data generator
IndividualDataPP Individual Data Pre-Processing
install_pyresurv Install Python Environment for ReSurv
ooslkh Compute the out-of-sample likelihood
ooslkh.default Compute the out-of-the sample likelihood
ooslkh.ReSurvFit Compute the out-of-the sample likelihood
pkg.env Helper functions
plot.ReSurvFit Plot for machine learning models
plot.ReSurvPredict Plot of the development factors
predict.ReSurvFit Predict IBNR frequency
print.summaryReSurvPredict Print summary of IBNR predictions
ReSurv Fit 'ReSurv' models on the individual data.
ReSurv.default Fit 'ReSurv' models on the individual data.
ReSurv.IndividualDataPP Fit 'ReSurv' models on the individual data.
ReSurvCV K fold cross-validation of a 'ReSurv' model.
ReSurvCV.default K fold cross-validation of ReSurv model.
ReSurvCV.IndividualDataPP K fold cross-validation of ReSurv model.
summary.ReSurvPredict Summary of IBNR predictions
survival_crps Survival continuously ranked probability score.
survival_crps.default Survival continuously ranked probability score.
survival_crps.ReSurvFit Survival continuously ranked probability score.