Package index • insurancerating

Construct tariff classes

fit_gam(): Generalized additive model

construct_tariff_classes(): Construct insurance tariff classes

autoplot(<fitgam>): Automatically create a ggplot for objects obtained from fit_gam()

autoplot(<constructtariffclasses>): Automatically create a ggplot for objects obtained from construct_tariff_classes()

Univariate analysis

Calculate and plot basic risk indicators split by the levels of a discrete risk factor in an insurance portfolio

univariate(): Univariate analysis for discrete risk factors

autoplot(<univariate>): Automatically create a ggplot for objects obtained from univariate()

histbin(): Create a histogram with outlier bins

restrict_coef() experimental: Restrict coefficients in the model

smooth_coef() experimental: Smooth coefficients in the model

update_glm() experimental: Refitting Generalized Linear Models

refit_glm() experimental: Refitting Generalized Linear Models

model_data() experimental: Get model data

construct_model_points() experimental: Construct model points from Generalized Linear Model

autoplot(<restricted>) experimental: Automatically create a ggplot for objects obtained from restrict_coef()

autoplot(<smooth>) experimental: Automatically create a ggplot for objects obtained from smooth_coef()

Rating factors

Calculate and plot rating factors obtained from (multiple) (generalized) lineair model objects

rating_factors(): Include reference group in regression output

autoplot(<riskfactor>): Automatically create a ggplot for objects obtained from rating_factors()

Data sets

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.

Performance and validation

Model quality and performance metrics

check_residuals(): Check model residuals

autoplot(<check_residuals>): Automatically create a ggplot for objects obtained from check_residuals()

check_overdispersion(): Check overdispersion of Poisson GLM

model_performance(): Performance of fitted GLMs

rmse(): Root Mean Squared Error

bootstrap_rmse(): Bootstrapped RMSE

autoplot(<bootstrap_rmse>): Automatically create a ggplot for objects obtained from bootstrap_rmse()

Additional

Often used in insurance ratings

biggest_reference(): Set reference group to the group with largest exposure

add_prediction(): Add predictions to a data frame

fisher(): Fisher's natural breaks classification

period_to_months(): Split period to months

rows_per_date(): Find active rows per date

reduce(): Reduce portfolio by merging redundant date ranges

summary(<reduce>): Automatically create a summary for objects obtained from reduce()

fit_truncated_dist() experimental: Fit a distribution to truncated severity (loss) data

autoplot(<truncated_dist>): Automatically create a ggplot for objects obtained from fit_truncated_dist()

rlnormt(): Generate data from truncated lognormal distribution

rgammat(): Generate data from truncated gamma distribution