See hubUtils::as_model_out_tbl()
for details.
Examples
if (requireNamespace("hubData", quietly = TRUE)) {
library(dplyr)
hub_path <- system.file("testhubs/flusight", package = "hubUtils")
hub_con <- hubData::connect_hub(hub_path)
hub_con %>%
filter(output_type == "quantile", location == "US") %>%
collect() %>%
filter(forecast_date == max(forecast_date)) %>%
as_model_out_tbl()
}
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
#> # A tibble: 92 × 8
#> model_id forecast_date horizon target location output_type output_type_id
#> * <chr> <date> <int> <chr> <chr> <chr> <chr>
#> 1 hub-baseline 2023-05-08 1 wk ah… US quantile 0.01
#> 2 hub-baseline 2023-05-08 1 wk ah… US quantile 0.025
#> 3 hub-baseline 2023-05-08 1 wk ah… US quantile 0.05
#> 4 hub-baseline 2023-05-08 1 wk ah… US quantile 0.1
#> 5 hub-baseline 2023-05-08 1 wk ah… US quantile 0.15
#> 6 hub-baseline 2023-05-08 1 wk ah… US quantile 0.2
#> 7 hub-baseline 2023-05-08 1 wk ah… US quantile 0.25
#> 8 hub-baseline 2023-05-08 1 wk ah… US quantile 0.3
#> 9 hub-baseline 2023-05-08 1 wk ah… US quantile 0.35
#> 10 hub-baseline 2023-05-08 1 wk ah… US quantile 0.4
#> # ℹ 82 more rows
#> # ℹ 1 more variable: value <dbl>