High-level delay parameters

Arguments

delays	List of delays, with flexible structure. Each delay in the `delays` list can be one of: a list representing a distribution object a discretized delay distribution vector a discretized delay distribution matrix a dataframe containing empirical delay data
delay	Single delay or list of delays. Each delay can be one of: a list representing a distribution object a discretized delay distribution vector a discretized delay distribution matrix a dataframe containing empirical delay data
delay_distribution_final_report	Distribution of the delay between the events collected in the incidence data and the a posteriori observations of these events.
gap_to_present	Integer. Default value: 0. Number of time steps truncated off from the right tail of the raw incidence data. See Details for more details.
cutoff_observation_probability	value between 0 and 1. Only datapoints for timesteps that have a probability of observing a event higher than `cutoff_observation_probability` are kept. The few datapoints with a lower probability to be observed are trimmed off the tail of the timeseries.
is_partially_reported_data	boolean. Set to `TRUE` if `incidence_data` represents delayed observations of infection events that themselves rely on further-delayed observations.
delay_until_partial	Single delay or list of delays. Each delay can be one of: a list representing a distribution object a discretized delay distribution vector a discretized delay distribution matrix a dataframe containing empirical delay data
delay_until_final_report	Single delay or list of delays. Each delay can be one of: a list representing a distribution object a discretized delay distribution vector a discretized delay distribution matrix a dataframe containing empirical delay data
partial_observation_requires_full_observation	boolean Set to `TRUE` if `partially_delayed_incidence` represent delayed observations of infection events that themselves rely on further-delayed observations. See Details for more details.