yrs_plot: Plot results for predicting license buying
In southwick-associates/lifetime: Provide functions for lifetime pricing

Description Usage Arguments See Also Examples

It's useful to visualize the results with retention estimates over time, especially for comparing alternative methods. This function takes the result of yrs_result and plots with some useful labelling and scaling.

1	yrs_plot(result_df, include_label = TRUE, xlim = 74, grp = method)

`result_df`	results returned from `yrs_result`
`include_label`	if TRUE, displays the method name and years estimate next to the line
`xlim`	maximum x-axis limit for plot
`grp`	unquoted name of grouping variable

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

library(dplyr)
library(ggplot2)

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))

# comparing retention-based vs avg-years-based methods
observe <- yrs_result_observe(df_split)
retain <- yrs_result_retain(df_split)
max <- yrs_result_max(df_split)
bind_rows(retain, max, avg) %>% yrs_plot() + geom_point(data = observe)

# comparing retain & renew methods
renew <- yrs_result_renew(df_split)
bind_rows(retain, renew) %>% yrs_plot() + geom_point(data = observe)

# using a GAM for retain
retain <- df_split %>%
    yrs_result_retain(model = function(x) yrs_fit_retain_gam(x))
bind_rows(retain, max, avg) %>% yrs_plot() + geom_point(data = observe)