baseline_forecaster: Baseline forecaster
In dshemetov/evalcast-mirror: Tools For Evaluating COVID Forecasters

The "flat-line" forecaster, which essentially mirrors the baseline in the COVID Forecast Hub. It augments a flat-line point prediction with a forecast distribution around this point based on quantiles of symmetrized week-to-week residuals.

baseline_forecaster(
  df_list,
  forecast_date,
  incidence_period = c("epiweek", "day"),
  ahead = 1:4,
  symmetrize = TRUE
)

`df_list`	list of data of the format that is returned by `covidcast::covidcast_signal()` or `covidcast::covidcast_signals()`.
`forecast_date`	Date object or string of the form "YYYY-MM-DD", indicating date on which forecasts will be made about some period (e.g., epiweek). For example, if `forecast_date = "2020-05-11"`, `incidence_period = "day"`, and `ahead = 3`, then, we'd be making forecasts for "2020-05-14".
`incidence_period`	String indicating the incidence period, either "epiweek" or "day".
`ahead`	Vector of (one or more) integers. How many epiweeks/days ahead are you forecasting? If `incidence_period = "epiweek"` and forecast_date is Sunday or Monday, then `ahead = 1` means the epiweek that includes the forecast date; if `forecast_date` falls on a Tuesday through Saturday, then it is the following epiweek. If `incidence_period = "day"`, then `ahead = 1` means the day after forecast date.
`symmetrize`	Should symmetrized residuals be used, or unsymmetrized (raw) residuals? Default is `TRUE`, which results in the flat-line point prediction. If `FALSE`, then point predictions can be increasing or decreasing, depending on the historical trend.

Data frame with columns ahead, geo_value, quantile, value. The quantile column gives the predicted quantiles of the forecast distribution for that location and ahead. An NA indicates a point forecast (same as the median in this case).

dshemetov/evalcast-mirror documentation built on Feb. 4, 2022, 8:52 a.m.