Updates Forecast Horizon Based on Input Data and Target

Makes sure that a forecast is returned for the user specified time period beyond the target date.

Usage

update_horizon(horizon, target_date, data)

horizon: Numeric, defaults to 7. Number of days into the future to forecast.
target_date: Date, defaults to maximum found in the data if not specified.
data: A <data.frame> of disease reports (confirm) by date (date). confirm must be numeric and date must be in date format. Optionally, data can also have a logical accumulate column which indicates whether data should be added to the next data point. This is useful when modelling e.g. weekly incidence data. See also the fill_missing() function which helps add the accumulate column with the desired properties when dealing with non-daily data. If any accumulation is done this happens after truncation as specified by the truncation argument. If all entries of confirm are missing (NA) the returned estimates will represent the prior distributions.

Numeric forecast horizon adjusted for the users intention