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 |