add_prediction | Add predictions to a data frame |
autoplot.bootstrap_rmse | Automatically create a ggplot for objects obtained from bootstrap_rmse() |
autoplot.check_residuals | Automatically create a ggplot for objects obtained from check_residuals() |
autoplot.constructtariffclasses | Automatically create a ggplot for objects obtained from construct_tariff_classes() |
autoplot.fitgam | Automatically create a ggplot for objects obtained from fit_gam() |
autoplot.restricted | Automatically create a ggplot for objects obtained from restrict_coef() |
autoplot.riskfactor | Automatically create a ggplot for objects obtained from rating_factors() |
autoplot.smooth | Automatically create a ggplot for objects obtained from smooth_coef() |
autoplot.truncated_dist | Automatically create a ggplot for objects obtained from fit_truncated_dist() |
autoplot.univariate | Automatically create a ggplot for objects obtained from univariate() |
biggest_reference | Set reference group to the group with largest exposure |
bootstrap_rmse | Bootstrapped RMSE |
check_overdispersion | Check overdispersion of Poisson GLM |
check_residuals | Check model residuals |
construct_model_points | Construct model points from Generalized Linear Model |
construct_tariff_classes | Construct insurance tariff classes |
fisher | Fisher's natural breaks classification |
fit_gam | Generalized additive model |
fit_truncated_dist | Fit a distribution to truncated severity (loss) data |
histbin | Create a histogram with outlier bins |
model_data | Get model data |
model_performance | Performance of fitted GLMs |
MTPL | Characteristics of 30,000 policyholders in a Motor Third Party Liability (MTPL) portfolio. |
MTPL2 | Characteristics of 3,000 policyholders in a Motor Third Party Liability (MTPL) portfolio. |
period_to_months | Split period to months |
rating_factors | Include reference group in regression output |
reduce | Reduce portfolio by merging redundant date ranges |
refit_glm | Refitting Generalized Linear Models |
restrict_coef | Restrict coefficients in the model |
rgammat | Generate data from truncated gamma distribution |
rlnormt | Generate data from truncated lognormal distribution |
rmse | Root Mean Squared Error |
rows_per_date | Find active rows per date |
smooth_coef | Smooth coefficients in the model |
summary.reduce | Automatically create a summary for objects obtained from reduce() |
univariate | Univariate analysis for discrete risk factors |
update_glm | Refitting Generalized Linear Models |