Title: A Collection of Insurance Datasets Useful in Risk Classification
Author: Alicja Wolny--Dominiak and Michal Trzesiok
Description: Insurance datasets, which are often used in claims severity and claims frequency modelling. It helps testing new regression models in those problems, such as GLM, GLMM, HGLM, non-linear mixed models etc. Most of the data sets are applied in the project "Mixed models in ratemaking" supported by grant NN 111461540 from Polish National Science Center.

Title: Analytic Insurance Rating Techniques
Description: Methods for insurance rating. It provides a data driven strategy for the construction of
insurance tariff classes. This strategy is based on the work by Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>.
The package also adds functionality showing additional lines for the reference
categories in the levels of the coefficients in the output of a generalized linear regression analysis.
In addition it implements a procedure determining the level of a factor with the largest exposure,
and thereafter changing the base level of the factor to this level.

Imports: classInt, ggplot2, mgcv, rpart, stringr

Imports: classInt, evtree, ggplot2, mgcv, stringr

Imports: classInt, data.table, evtree, ggplot2, lubridate, mgcv,

Imports: classInt, data.table, dplyr, evtree, ggplot2, lubridate, mgcv,
Suggests: knitr, rmarkdown, scales, testthat

Authors@R: c(person("Martin", "Haringa", role = c("aut", "cre"), email = "mtharinga@gmail.com"))

insurancerating also provides recipes on how to easily perform univariate analyses on an insurance portfolio. In addition it
adds functionality to include reference categories in the levels of the coefficients in the output of a generalized linear
Imports: classInt, data.table, dplyr, evtree, ggplot2, lubridate,
magrittr, mgcv, patchwork, stringr, tidyr

Description: Methods for insurance rating. It helps actuaries to implement GLMs within all relevant steps needed to construct
a risk premium from raw data. It provides a data driven strategy for the construction of insurance tariff classes.
This strategy is based on the work by Antonio and Valdez (2012) <doi:10.1007/s10182-011-0152-7>. It also provides recipes
on how to easily perform one-way, or univariate, analyses on an insurance portfolio. In addition it adds functionality
to include reference categories in the levels of the coefficients in the output of a generalized linear regression analysis.
Imports: bayestestR, ciTools, classInt, data.table, dplyr, evtree,
ggplot2, insight, lubridate, magrittr, mgcv, patchwork,