NEWS.md

In actxps: Create Actuarial Experience Studies: Prepare Data, Summarize Results, and Create Reports

actxps 1.5.0

• 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

• 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

• 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

• 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

• 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

• 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

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

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

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

actxps documentation built on June 26, 2024, 9:07 a.m.