Analytic Insurance Rating Techniques

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Documentation for package ‘insurancerating’ version 0.6.5

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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.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_tariff_classes Construct insurance tariff classes
fisher Fisher's natural breaks classification
fit_gam Generalized additive model
histbin Create a histogram with outlier bins
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
rating_factors1 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
rmse Root Mean Squared Error
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