Flatline residuals in tidymodels framework are wrong

[dajmcdon]

Below, the .pred column should be the same (it is), but the residuals should be different.

library(epipredict)
library(purrr)
library(dplyr)
library(tidyr)

jhu <- case_death_rate_subset %>% 
  filter(time_value >= "2021-11-01", geo_value %in% c("pa", "ca", "ny"))

f7 <- flatline_forecaster(jhu, "death_rate", flatline_args_list(ahead = 7))
f14 <- flatline_forecaster(jhu, "death_rate", flatline_args_list(ahead = 14))

f7$predictions %>%
  mutate(q = nested_quantiles(.pred_distn)) %>% 
  unnest(q) %>% 
  pivot_wider(names_from = tau, values_from = q) %>%
  select(geo_value:.pred, target_date, `0.05`, `0.95`)
#> # A tibble: 3 × 6
#>   geo_value time_value .pred target_date `0.05` `0.95`
#>   <chr>     <date>     <dbl> <date>       <dbl>  <dbl>
#> 1 ca        2021-12-31 0.142 2022-01-07   0      0.392
#> 2 ny        2021-12-31 0.422 2022-01-07   0.172  0.672
#> 3 pa        2021-12-31 0.732 2022-01-07   0.482  0.982

f14$predictions %>%
  mutate(q = nested_quantiles(.pred_distn)) %>% 
  unnest(q) %>% 
  pivot_wider(names_from = tau, values_from = q) %>%
  select(geo_value:.pred, target_date, `0.05`, `0.95`)
#> # A tibble: 3 × 6
#>   geo_value time_value .pred target_date `0.05` `0.95`
#>   <chr>     <date>     <dbl> <date>       <dbl>  <dbl>
#> 1 ca        2021-12-31 0.142 2022-01-14   0      0.392
#> 2 ny        2021-12-31 0.422 2022-01-14   0.172  0.672
#> 3 pa        2021-12-31 0.732 2022-01-14   0.482  0.982

^{Created on 2023-06-09 with reprex v2.0.2}

Further tests suggest it is happening deep in the tidymodels processing of the workflow. It can't be replicated by calling flatline() directly.

jhu1 <- jhu %>% mutate(ld7 = lead(death_rate, 7), ld14 = lead(death_rate, 14))
f7a <- flatline(ld7 ~ geo_value + death_rate, jhu1)
f14a <- flatline(ld14 ~ geo_value + death_rate, jhu1)

quantile(residuals(f7a)$.resid, probs = c(0.05, 0.95), na.rm = TRUE)
#>         5%        95% 
#> -0.6987016  0.5442913
quantile(residuals(f14a)$.resid, probs = c(0.05, 0.95), na.rm = TRUE)
#>         5%        95% 
#> -0.5408296  0.7069717

^{Created on 2023-06-09 with reprex v2.0.2}