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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.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.exp_stats() is passed a weighting variable.summary() method for exposed_df objects that calls exp_stats().expose() functions was changed from the first observed status to the most common status.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.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.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-variableautoplot.exp_df() and autoplot.trx_df() can now create scatter plots if “points” is passed to the geoms argument.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
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().
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.autoplot() methods. These include plot_termination_rates() and plot_actual_to_expected() for termination studies and plot_utilization_rates() for transaction studiesexp_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(),add_predictions() and step_expose().autoplot() and autotable() methods?actxps)add_predictions() function that attaches one or more columns of model predictions to an exposed_df object or any other data frame.add_transactions() and autotable() functions for compatibility with the dplyr 1.1.1 and gt 0.9.0.The actxps package now contains support for transaction studies.
add_transactions() function adds transactions to exposed_df objects.trx_stats() function summarizes transaction results and returns a trx_df object.trx_df) S3 methods were added for for autoplot() and autotable().exp_shiny() function was updated to support transaction studies.withdrawals) and sample policy values (account_vals). These are meant to be paired with census_dat.vignette("transactions").Other changes
pol_interval() (a generic version), pol_yr(), pol_qtr(), pol_mth(), and pol_wk(). See vignette("misc").as_exposed_df() function to include stricter input requirements and helpful error messages.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().autotable.exp_df() was updated to be consistent across like columns.pol_val column in census_dat was renamed to premium.expose() functions now include a new column for period end dates.
Fixed issues with expose() dropping records:
Fixed 2 R CMD check problems.
First version submitted to CRAN.
Added exp_shiny() function.
Added step_expose() recipe step function.
First developmental version
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