Impulse response function for nested VAR models

Hi there,

I would like to know whether it is possible --after fitting a VAR model across different keys in a tsibble--to display the impulse response functions for each of the keys?

Here's a small example

weather <- nycflights13::weather %>% 
  dplyr::select(origin, time_hour, temp, humid, precip)

weather_ts <- as_tsibble(weather, key = origin, index = time_hour)

weather_day <- weather_ts %>%
    group_by(origin) %>%
    index_by(day = as.Date(time_hour)) %>%
    summarise(
      mean_temp = mean(temp),
      mean_humid = mean(humid),
      mean_precip = mean(precip)
    ) %>%
    update_tsibble(index = day)

fit <- weather_day %>%
  model(
    VAR(vars(mean_precip, mean_humid) ~ AR(1)))
    
fit_coef <- fit %>% 
  tidy(.) 

The example shows lagged effects, e.g., from precip to humidity, for three airports (origin). Now it would be nice to have a way to create a IRF plot for the three keys and scale it to many more keys (although this would surely be messy at some point).

Thanks for suggestions,
Holger

Start with the grouped tsibble example using model(VAR(vars(mean_precip, mean_humid) ~ AR(1))) and its tidy(.) output. Investigate how impulse response functions could be represented and plotted for each origin key, then define an interface that scales beyond the three-airport example. Done means a documented, tested approach for producing IRF plots across nested VAR models.