yrs_result: Results of license buying
In southwick-associates/lifetime: Provide functions for lifetime pricing

Description Usage Arguments Functions See Also Examples

These are convenience functions to wrap calculating, fitting, and predicting.

yrs_result_observe(history_split, predict_age = 30)

yrs_result_retain(history_split, predict_age = 30, end_age = 64,
  model = function(x) yrs_fit_retain(x))

yrs_result_renew(history_split, history_predict = NULL,
  predict_age = 30, end_age = 64)

yrs_result_max(history_split, predict_age = 30, end_age = 64)

yrs_result_avg(history, predict_age = 30, end_age = 64)

`history_split`	license history list produced by yrs_zero_split()
`predict_age`	target age for prediction (year zero)
`end_age`	last age for prediction
`model`	function for modelling
`history_predict`	prediction dataset. If NULL, uses the training dataset
`history`	training dataset

yrs_result_observe: Results for predicting license buying - observed retention
yrs_result_retain: Results for predicting license buying - predicted retention
yrs_result_renew: Results for predicting license buying - predicted renewal
yrs_result_max: Results for predicting license buying - maximum retention

Based on observed retention, assume the retention rate remains level after the last observed year. This defines a maximum estimate because retention curves never begin sloping upward.
yrs_result_avg: Results for predicting license buying - predicted avg years

Different than the renew & retain functions since it uses all available ages to estimate average years purchased in five, so no train_ages arguments are needed.

Other functions to estimate annual license buying: yrs_avidity, yrs_calc_avg, yrs_calc, yrs_fit, yrs_lifetime, yrs_plot, yrs_predict_avg, yrs_predict, yrs_zero

library(dplyr)
data(all_sports)
avg <- yrs_result_avg(all_sports)

df_split <- all_sports %>%
    yrs_avidity(drop_na_yrs = FALSE) %>%
    yrs_zero_split() %>%
    yrs_zero_filter(function(x) filter(x, age_year %in% 25:35))

observe <- yrs_result_observe(df_split)
retain <- yrs_result_retain(df_split)
renew <- yrs_result_renew(df_split)
max <- yrs_result_max(df_split)

library(ggplot2)
ggplot(observe, aes(age_year, pct, color = method)) + geom_point() +
    geom_line(data = retain) +
    geom_line(data = renew) +
    geom_line(data = avg) +
    geom_line(data = max)