## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) actxps:::set_actxps_plot_theme() ## ----packages, message=FALSE, warning=FALSE----------------------------------- library(actxps) library(dplyr) census_dat ## ----status-count------------------------------------------------------------- (status_counts <- table(census_dat$status)) ## ----naive-------------------------------------------------------------------- # incorrect prop.table(status_counts) ## ----example------------------------------------------------------------------ exposed_data <- expose(census_dat, end_date = "2019-12-31", target_status = "Surrender") exposed_data ## ----term-rate---------------------------------------------------------------- sum(exposed_data$status == "Surrender") / sum(exposed_data$exposure) ## ----stats-1------------------------------------------------------------------ exp_stats(exposed_data) ## ----stats-grouped------------------------------------------------------------ exp_res <- exposed_data |> group_by(pol_yr, inc_guar) |> exp_stats() exp_res ## ----stats-ae----------------------------------------------------------------- expected_table <- c(seq(0.005, 0.03, length.out = 10), 0.2, 0.15, rep(0.05, 3)) # using 2 different expected termination rates exposed_data <- exposed_data |> mutate(expected_1 = expected_table[pol_yr], expected_2 = ifelse(exposed_data$inc_guar, 0.015, 0.03)) exp_res <- exposed_data |> group_by(pol_yr, inc_guar) |> exp_stats(expected = c("expected_1", "expected_2")) exp_res ## ----plot, warning=FALSE, message=FALSE, dpi = 300---------------------------- autoplot(exp_res) ## ----table, eval = FALSE------------------------------------------------------ # # first 10 rows showed for brevity # exp_res |> head(10) |> autotable() ## ----summary-1---------------------------------------------------------------- summary(exp_res) ## ----summary-2---------------------------------------------------------------- summary(exp_res, inc_guar) ## ----shiny, eval = FALSE------------------------------------------------------ # exp_shiny(exposed_data)