align_forecasts | R Documentation |
Add reference dates and relative horizons to a dataframe of forecasts
align_forecasts(
forecasts,
reference_dates = list(wk = NULL, day = NULL),
reference_weekday = list(wk = "Saturday", day = "Monday"),
reference_windows = list(wk = -4:2, day = -6:0),
drop_nonpos_relative_horizons = TRUE
)
forecasts |
dataframe in format returned by |
reference_dates |
a named list of vectors of reference dates for
forecasts, grouping forecasts that were made during the same week. The list
should have two components: "wk" providing reference dates for forecasts at
a weekly temporal resolution, and "day" providing reference dates for
forecasts at a daily temporal resolution. Dates may be a character vector in
the format "YYYY-MM-DD" or a vector of Dates. For example, if a forecast of
daily hospitalizations is issued with a forecast date that is Saturday,
2021-09-04, and we want to align analyses around a Monday, the reference
date would be Monday, 2021-09-06. This can be accomplished more easily by
providing the |
reference_weekday |
a named list or named character vector of weekdays to use as reference dates. The list should contain entries named "wk" and "day". The default uses "Saturday" as the reference weekday for forecasts of weekly targets and "Monday" as the reference weekday for forecasts of daily targets. |
reference_windows |
a named list of integer vectors with offset values
giving the set of forecast dates that should be assigned to a particular
reference date, in units of number of days. The function defaults to using
|
drop_nonpos_relative_horizons |
boolean indicating whether forecasts that have a
non-positive horizon relative to the reference date should be dropped.
Defaults to |
forecast dataframe augmented by columns reference_date and relative_horizon
## Not run:
library(tidyverse)
library(covidHubUtils)
hub_repo_path <- "../covid19-forecast-hub"
dates <- seq.Date(as.Date("2021-05-01"), as.Date("2021-06-01"), by = 1)
forecasts <- load_forecasts(
models = get_all_models(source = "local_hub_repo", hub_repo_path = hub_repo_path),
dates = dates[!(weekdays(dates) %in% c("Monday", "Sunday"))],
date_window_size = 0,
locations = "US",
types = "quantile",
source = "local_hub_repo",
hub_repo_path = hub_repo_path,
verbose = FALSE,
as_of = NULL,
hub = c("US")
) %>% filter(quantile == .5)
forecasts
forecasts %>% distinct(model)
forecasts %>% align_forecasts()
forecasts %>% align_forecasts(drop_nonpos_relative_horizons = FALSE) %>%
filter(relative_horizon <= 0)
## End(Not run)
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