insurancerating 0.6.9

• refit_glm() is renamed to update_glm()
• construct_model_points() and model_data() are added to create model points

insurancerating 0.6.8

• show_total in autoplot.univariate() is added to add line for total of groups in case by is used in univariate(); total_color can be used to change the color of the line, and total_name is added to change the name of the legend for the line
• rating_factors() now accepts GLMs with an intercept only
• fit_truncated_dist() is added to fit the original distribution (gamma, lognormal) from truncated severity data
• join_to_nearest() now returns NA in case NA is used as input

insurancerating 0.6.7

• smooth_coef() now returns an error message when intervals are not obtained by cut()
• get_data() is added to return the data used in refit_glm()

insurancerating 0.6.6

• summary.reduce() now gives correct aggregation for periods “months” and “quarters”
• rows_per_date() is added to determine active portfolio for a certain date

insurancerating 0.6.5

• smooth_coef() and restrict_coef() are added for model refinement
• histbin() now uses darkblue as default fill color

insurancerating 0.6.4

• In summary.reduce(), name can be used to change the name of the new column in the output.
• Dataset MTPL now contains extra columns for power, bm, and zip.
• Some functions in insight are renamed, therefore insight::format_table() is replaced with insight::export_table().

insurancerating 0.6.3

• fit_gam() for pure premium is now using average premium for each x calculated as sum(pure_premium * exposure) / sum(exposure) instead of sum(pure_premium) / sum(exposure) (#2).
• histbin() is added to create histograms with outliers
• reduce now returns a data.frame as output

insurancerating 0.6.2

• check_normality() is now depreciated; use check_residuals() instead to detect overall deviations from the expected distribution
• rating_factors() now shows significance stars for p-values
• period_to_months() arithmetic operations with dates are rewritten; much faster
• univariate() now has argument by to determine summary statistics for different subgroups

insurancerating 0.6.1

• univariate_all() and autoplot.univ_all() are now depreciated; use univariate() and autoplot.univariate() instead
• check_overdispersion(), check_normality(), model_performance(), bootstrap_rmse(), and add_prediction() are added to test model quality and return performance metrics
• reduce() is added to reduce an insurance portfolio by merging redundant date ranges

insurancerating 0.6.0

• label_width in autoplot() is added to wrap long labels in multiple lines
• sort_manual in autoplot() is added to sort risk factors into an own ordering
• autoplot() now works without manually loading package ggplot2 and patchwork first
• rating_factors() now returns an object of class riskfactor
• autoplot.riskfactor() is added to create the corresponding plots to the output given by rating_factors()

insurancerating 0.5.2

• autoplot.univ_all() now gives correct labels on the x-axis when ncol > 1.

insurancerating 0.5.1

• A package website is added using pkgdown.
• construct_tariff_classes() and fit_gam() now only returns tariff classes and fitted gam respectively; other items are stored as attributes.
• univariate_frequency(), univariate_average_severity(), univariate_risk_premium(), univariate_loss_ratio(), univariate_average_premium(), univariate_exposure(), and univariate_all() are added to perform an univariate analysis on an insurance portfolio.
• autoplot() creates the corresponding plots to the summary statistics calculated by univariate_*.

insurancerating 0.5.0

• construct_tariff_classes() is now split in fit_gam() and construct_tariff_classes().
• A vignette is added on how to use the package.

insurancerating 0.4.3

• period_to_months() is added to split rows with a time period longer than one month to multiple rows with a time period of exactly one month each.

insurancerating 0.4.2

• In construct_tariff_classes(), model now also accepts ‘severity’ as specification.