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Changelog

Source: NEWS.md

insurancerating (development version)

Main API updates

Portfolio analysis

  • factor_analysis() is now the primary function for univariate/factor-level portfolio analysis. It returns objects with primary class "factor_analysis" while retaining "univariate" for compatibility.
  • plot_severity_distribution() was added for exploratory severity diagnostics by category. It shows individual claim observations with mean and median markers, optional direct labels, and optional firebrick highlighting for claims above a user-supplied threshold.
  • univariate() is deprecated and remains available as a compatibility wrapper. The old NSE interface is still supported through the deprecated wrapper.
  • factor_analysis() now validates metric columns and grouping variables early, with clearer error messages for missing columns.
  • Metrics with a zero or missing denominator now return NA_real_ instead of Inf or NaN.
  • autoplot.factor_analysis() is the primary plot method. The deprecated show_plots argument has been replaced by metrics.
  • The factor-analysis plot keeps the established package styling and now uses a consistent grid, axis-line, tick and secondary-axis style.

Outlier histograms

  • outlier_histogram() has clearer argument names: lower, upper, density, bar_fill, bar_color, tail_fill, tail_color, and density_color.
  • Deprecated argument names remain supported: left, right, line, fill, color, and fill_outliers.
  • The default colours now align with the package palette: light grey bars, orange tail bins, and blue density curve.
  • Input validation has been expanded for missing columns, non-numeric variables, invalid cutoffs, invalid colours, invalid bin counts, constant variables and all-missing variables.
  • histbin() is deprecated and remains available as a compatibility wrapper.

Risk factor GAMs and tariff segmentation

  • risk_factor_gam() is the primary spelling for fitting GAMs to continuous risk factors. riskfactor_gam() and fit_gam() remain available for compatibility, with fit_gam() deprecated.
  • risk_factor_gam() returns objects with primary class "risk_factor_gam"; compatibility classes are retained for older code.
  • model = "pure_premium" replaces the older model = "burning" wording. The old value remains supported with a lifecycle warning.
  • Input validation and documentation for frequency, severity and pure-premium GAMs have been improved.
  • derive_tariff_segments() replaces construct_tariff_classes() as the primary API for deriving tariff segments from a fitted risk-factor GAM.
  • derive_tariff_segments() returns objects with primary class "tariff_segments".
  • add_tariff_segments() can add derived tariff segments back to a portfolio.
  • construct_tariff_classes() remains available as a deprecated compatibility wrapper.
  • Split extraction now handles decimal split points correctly.
  • Tree-fitting and split-extraction failures now fail clearly instead of silently returning one broad tariff interval.
  • The tariff-segment plot now recognises confidence interval columns produced by the package’s own GAM output.

Rating tables

Prediction helpers

  • add_prediction() now has clearer naming arguments: predictions, prefix, confidence, and interval_names.
  • var and conf_int are deprecated in favour of predictions and confidence.
  • Confidence interval columns now use _lower and _upper suffixes by default.
  • The function now validates alpha, confidence settings, duplicate output names, name collisions with existing columns, missing models and non-GLM inputs.

Model data and rating grids

  • extract_model_data() replaces model_data() as the primary API for extracting model data from fitted models.
  • model_data() is deprecated and remains available as a wrapper.
  • rating_grid() now uses base R internally and returns a regular data.frame.
  • Plain GLM metadata extraction has been improved so rating_grid(glm) groups by model terms as expected.
  • Refinement metadata is now joined by the related original/new factor columns instead of being cross-joined onto every rating-grid row.

Model refinement

  • The refinement API has been clarified around prepare_refinement() |> add_*() |> refit().
  • A new excess-loss workflow was added for capped severity and pure-premium modelling: assess_excess_threshold(), calculate_excess_loss(), allocate_excess_loss() and add_excess_loading().
  • assess_excess_threshold() compares candidate large-loss thresholds and shows the impact on excess loss, capped loss and pure premium.
  • calculate_excess_loss() now performs only the deterministic historical decomposition into capped and excess claim amounts.
  • allocate_excess_loss() handles allocation, pooling and bootstrap uncertainty modelling. It supports observed or bootstrap excess burdens, portfolio, group-level and partial pooling, and optional severity noise in the bootstrap.
  • allocate_excess_loss() now uses preserve_total = TRUE by default so that partial pooling redistributes the selected excess burden without changing the total allocated excess loss.
  • add_excess_loading() adds the allocated excess loading to pricing data and returns base_premium, excess_loading and loaded_premium.
  • add_excess_loading() now treats premium amounts as the default workflow and keeps the distinction between absolute allocated_excess_loss and per-weight allocated_loading explicit.
  • add_smoothing() now uses model_variable and source_variable as the primary argument names.
  • edit_smoothing() now uses clearer in-object editing arguments for adjusting smoothing settings without supplying an external data frame.
  • add_restriction() can now accept a partial restriction data frame. Missing levels are automatically filled with the already fitted GLM relativities, so users can adjust only selected levels.
  • add_relativities() now uses model_variable and split_variable.
  • relativities() replaces relativities_list() as the helper for building relativity specifications.
  • restrict_coef(), smooth_coef() and refit_glm() remain deprecated compatibility wrappers and now link clearly to add_restriction(), add_smoothing() and refit().
  • autoplot.rating_refinement() no longer carries an experimental badge and uses the package plot theme.
  • The refinement documentation has been expanded with applied examples and a clearer explanation of smoothing, restrictions, relativities and refitting.

Reference levels

  • set_reference_level() replaces biggest_reference() as the primary helper for choosing factor reference levels.
  • The default method is method = "largest_weight".
  • A manual level argument was added so a specific reference level can be selected explicitly.
  • biggest_reference() remains available as a deprecated compatibility wrapper.

Time utilities

Model validation and performance

  • bootstrap_performance() now has an explicit metric = "rmse" argument.
  • sampling = c("bootstrap", "split") was added to distinguish bootstrap out-of-bag evaluation from split validation.
  • Deprecated arguments n and frac remain supported as aliases for n_resamples and sample_fraction.
  • Character and factor rating variables are handled more robustly across resamples so prediction does not fail when a level is absent from a training sample.
  • autoplot.bootstrap_performance() now uses a package-consistent visual style: subtle grey histogram, transparent blue density, orange original-model reference line, subtle confidence interval lines and no gap between the bars and x-axis.
  • bootstrap_rmse() remains available as a deprecated compatibility wrapper and returned objects retain class "bootstrap_rmse" for older code.
  • check_overdispersion() now validates non-GLM input, checks for Poisson models and fails clearly when residual degrees of freedom are not positive.
  • print.overdispersion() now bases its conclusion on the original p-value rather than a rounded display value.
  • check_residuals() now validates inputs, uses all scaled residuals for the KS test, handles empty residual vectors clearly and documents the DHARMa-based residual workflow for actuarial users.
  • autoplot.check_residuals() now has a controllable max_points argument and uses ASCII messages and the package plot theme.

Truncated severity distributions

  • fit_truncated_severity() replaces fit_truncated_dist() as the primary API for fitting distributions to truncated claim severities.
  • Returned objects use primary class "truncated_severity" while compatibility with "truncated_dist" is retained.
  • fit_truncated_dist() remains available as a deprecated compatibility wrapper.
  • Observations outside the truncation interval now fail clearly instead of only warning and continuing.
  • Validation has been expanded for truncation bounds, optimisation starts, grid sizes, reporting options and random generator arguments.
  • Public random generators rlnormt() and rgammat() now validate sample size, distribution parameters, finite intervals and positive truncation mass.
  • Plot argument names were modernised to ecdf_geom, x_label, y_label, show_title, digits and truncation_digits, with old names supported for compatibility.

Fisher-Jenks classification

  • fisher_classify() and fisher() are deprecated because Fisher-Jenks classification is a general-purpose grouping method and is not directly tied to the insurance-rating workflow.
  • classInt moved from Imports to Suggests.

Documentation, website and tests

  • The README and vignettes have been revised to present the package as a set of actuarial pricing building blocks rather than a prescribed pricing method.
  • The former “Pricing principles” vignette was replaced by “Pricing workflow building blocks”.
  • The refinement vignette was rewritten with a more practical tone and current API examples.
  • pkgdown reference sections were reorganised; deprecated functions are grouped under “Deprecated” and internal S3 methods are no longer listed as primary reference topics.
  • New and expanded tests cover tariff segmentation, rating tables, observed experience plotting, refinement workflows, model-data extraction, model performance, overdispersion, residual checks, outlier histograms, truncated distributions, time utilities and factor analysis.

insurancerating 0.7.5

CRAN release: 2024-10-09

  • rating_factors() now always returns correct output when column with exposure in data is not named exposure
  • intercept_only in update_glm() is added to apply the manual changes and refit the intercept, ensuring that the changes have no impact on the other variables.
  • smoothing in smooth_coef() is added to choose smoothing specification
  • The README has been revised

insurancerating 0.7.4

CRAN release: 2024-05-20

  • bootstrap_rmse() now uses after_stat(density) instead of the deprecated dot-dot notation
  • custom_theme in autoplot.univariate() is added to customize the theme

insurancerating 0.7.3

CRAN release: 2024-05-09

  • autoplot.univariate() now generates a plot even when there are missing values in the rows
  • rating_factors() now always returns the correct coefficients when used on a ‘refitsmooth’ or ‘refitrestricted’ class of GLM.

insurancerating 0.7.2

CRAN release: 2022-12-20

insurancerating 0.7.1

CRAN release: 2022-09-06

  • rotate_angle in autoplot.univariate() is added to rotate x-labels
  • univariate() now accepts external vectors for x; vec_ext() must be used

insurancerating 0.7.0

CRAN release: 2022-07-08

  • smooth_coef() now gives correct results for intervals with scientific notation
  • reduce() now returns no errors anymore for columns with dates in POSIXt format

insurancerating 0.6.9

CRAN release: 2021-12-11

insurancerating 0.6.8

CRAN release: 2021-11-10

  • 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

CRAN release: 2021-07-28

  • 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

CRAN release: 2021-05-19

  • 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

CRAN release: 2021-03-22

insurancerating 0.6.4

CRAN release: 2021-01-12

  • 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

CRAN release: 2020-10-28

  • 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

CRAN release: 2020-06-08

  • 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

CRAN release: 2020-04-29

insurancerating 0.6.0

CRAN release: 2020-04-10

  • 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

CRAN release: 2020-03-30

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

insurancerating 0.5.1

CRAN release: 2020-03-29

  • 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

CRAN release: 2020-03-12

insurancerating 0.4.3

CRAN release: 2019-11-01

  • 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

CRAN release: 2019-05-31