Changelog

Source: NEWS.md

actxps (development version)

• New feature - control variables

  • exp_stats() has two new arguments: control_vars and control_distinct_max.
  • Control variables are used to estimate the impact of any grouping variables on observed experience after accounting for the impact of control variables. The idea here is that experience is first summarized across the control variables to derive a new expected values basis. This expected values basis is then used to calculate actual-to-expected ratios.
  • The control_distinct_max argument places an upper limit on the maximum number of unique values allowed in any control variable.
  • exp_shiny() now includes a control variable selection widget.

• Added the “cli” package to replace “rlang” for certain errors, warnings, and messages.

• Various small typo fixes.

actxps 1.5.0

CRAN release: 2024-06-25

• expose_split() bug fixes:

  • expose_split() was updated to respect the values of start_date and end_date originally passed to the expose() function.
  • Future policy anniversary dates falling on February 29th leap days are now consistent with expose()
  • New tests were added to verify that the sum of policy year exposures (exposure_pol) after calling expose_split() match exposures produced by expose_py().

• The expose() family of functions and add_transactions() now allow date columns to be passed as character vectors in YYYY-MM-DD format. Any character vectors are converted to dates behind-the-scenes, and any missing values will results in an error message.

• To improve the speed of date calculations, lubridate was replaced with the clock package. Lubridate is no longer included in Imports.

• Breaking change - The pol_interval() function is no longer exported. As part of the removal of lubridate, this function’s dur_length argument only accepts, “year”, “quarter”, “month”, or “week”.

• Shiny app layout updates

• Small vignette and documentation clean-ups

actxps 1.4.0

CRAN release: 2023-11-26

• actxps now supports split exposures that divide calendar periods crossing policy anniversaries into pre-anniversary and post-anniversary records. The function expose_split() can convert any exposed_df object with calendar period exposures (yearly, quarterly, monthly, or weekly) into a split_exposed_df object. Split exposure data frames contain columns for exposures both on a calendar period and policy year basis.
• exp_stats() and exp_shiny() now require clarification as to which exposure basis should be used when passed a split_exposed_df object.
• All expose_df objects now contains a default_status attribute.
• autotable() functions now contain the arguments decimals_amt and suffix_amt. The former allows one to specify the number of decimals appearing after amount columns. The latter is used to automatically scale large numbers into by thousands, millions, billions, or trillions.
• Corrected an error in the calculation of the standard deviations of claims when exp_stats() is passed a weighting variable.
• Added a summary() method for exposed_df objects that calls exp_stats().
• The assumed default status in expose() functions was changed from the first observed status to the most common status.
• The functions as_exp_df() and as_trx_df() were added to convert pre-aggregated experience studies to the exp_df and trx_df formats, respectively.
• agg_sim_dat - a new simulated data set of pre-aggregated experience was added for testing as_exp_df() and as_trx_df().
• is_exp_df() and as_trx_df() were added to test for the exp_df and trx_df classes.

actxps 1.3.0

CRAN release: 2023-09-15

• A new conf_int argument was added to exp_stats() that creates confidence intervals around observed termination rates, credibility-weighted termination rates, and any actual-to-expected ratios.

• Similarly, conf_int was added to trx_stats() to create confidence intervals around utilization rates and any “percentage of” output columns. A conf_level argument was also added to this function.

• autoplot.exp_df() and autoplot.trx_df() now have a conf_int_bars argument that plots confidence intervals (if available) as error bars for the selected y-variable

• autoplot.exp_df() and autoplot.trx_df() can now create scatter plots if “points” is passed to the geoms argument.

• The second y-axis in the autoplot() methods was updated to use an area geometry instead of bars for discrete x-axis variables. In addition, when a log-10 y-scale is used, areas will always be positive quantities. Previously, it was observed that areas were drawn as negative values for y-values on the main scale less than 1.

• autotable.exp_df() and autotable.trx_df() were updated to format intervals.

• exp_shiny() updates

  • The layout and theme were updated in to align with changes made in shiny 1.7.5 and bslib 0.5.1
  • The function now includes the ability to customize the Bootstrap theme
  • Plots can now be re-sized and viewed in full screen mode
  • Tables contain new customization options and can be viewed in full screen mode
  • Tables and plots can be exported
  • Both the plots and tables optionally include confidence intervals
  • Tooltips were added throughout to explain the UI
  • A play / pause button was added to suspend interactivity on demand
  • A description of filters was added to the sidebar

• Breaking change - The confidence level argument cred_p was renamed to conf_level. This change was made because the confidence level is no longer strictly used for credibility calculations. This change impacts the functions exp_stats() and exp_shiny().

actxps 1.2.0

CRAN release: 2023-08-09

• autoplot.exp_df() and autoplot.trx_df() now include new options for adding a second y-axis and plotting results on a log-10 scale. The second y-axis defaults to plotting exposures using an area geometry.
• New plotting functions were added to create common experience analysis plots that were not simple to create using autoplot() methods. These include plot_termination_rates() and plot_actual_to_expected() for termination studies and plot_utilization_rates() for transaction studies
• The exp_shiny() function received a handful of updates to accommodate new plotting functions and options. A small performance improvement was added in filtering logic as well. New options include a title input, credibility options taken from exp_stats(),
• A new vignette was added on data visualization.
• The miscellaneous vignette was updated to include examples for add_predictions() and step_expose().
• Examples were added to autoplot() and autotable() methods
• Help documentation was added for the package itself (?actxps)

actxps 1.1.0

CRAN release: 2023-05-07

• New add_predictions() function that attaches one or more columns of model predictions to an exposed_df object or any other data frame.
• Small updates to add_transactions() and autotable() functions for compatibility with the dplyr 1.1.1 and gt 0.9.0.

actxps 1.0.1

CRAN release: 2023-04-11

• Minor patch to a single test for compatibility with a future release of the recipes package.
• Various small documentation typo fixes

actxps 1.0.0

CRAN release: 2023-03-04

The actxps package now contains support for transaction studies.

• The add_transactions() function adds transactions to exposed_df objects.
• The trx_stats() function summarizes transaction results and returns a trx_df object.
• New transaction summary (trx_df) S3 methods were added for for autoplot() and autotable().
• The exp_shiny() function was updated to support transaction studies.
• New sample data sets were added with transactions (withdrawals) and sample policy values (account_vals). These are meant to be paired with census_dat.
• Added vignette("transactions").

Other changes

• A new family of functions were added to calculate policy durations. These include pol_interval() (a generic version), pol_yr(), pol_qtr(), pol_mth(), and pol_wk(). See vignette("misc").
• Several updates were made to the as_exposed_df() function to include stricter input requirements and helpful error messages.
• S3 methods for several dplyr functions were added for exposed_df objects to ensure class persistence, especially on grouped data frames. These include: group_by() and ungroup(), filter(), arrange(), mutate(), select(), slice(), rename(), relocate(), left_join(), right_join(), inner_join(), full_join(), semi_join(), and anti_join().
• The conditional formatting for color in autotable.exp_df() was updated to be consistent across like columns.
• The pol_val column in census_dat was renamed to premium.

actxps 0.2.1

CRAN release: 2023-02-11

expose() functions now include a new column for period end dates.

Fixed issues with expose() dropping records:

• Handling of leap days / years
• Correction to date addition to always rollback dates to the last day of the month.

Fixed 2 R CMD check problems.

actxps 0.2.0

CRAN release: 2022-08-31

First version submitted to CRAN.

Added exp_shiny() function.

actxps 0.1.0

Added step_expose() recipe step function.

actxps 0.0.9000

First developmental version