EpiNow2 (version 1.7.1)

simulate_secondary: Simulate secondary observations from primary observations

Description

Simulations are done from a given trajectory of primary observations by applying any given delays and observation parameters.

Usage

simulate_secondary(
  primary,
  day_of_week_effect = NULL,
  secondary = secondary_opts(),
  delays = delay_opts(),
  truncation = trunc_opts(),
  obs = obs_opts(),
  CrIs = c(0.2, 0.5, 0.9),
  backend = "rstan"
)

Value

A data.table of simulated secondary observations (column secondary) by date.

Arguments

primary

a data frame of primary reports (column primary) by date (column date). Column primary must be numeric and date must be in date format. it will be assumed that primary is zero on the missing days.

day_of_week_effect

either NULL (no day of the week effect) or a numerical vector of length specified in obs_opts() as week_length (default: 7) if week_effect is set to TRUE. Each element of the vector gives the weight given to reporting on this day (normalised to 1). The default is NULL.

secondary

A call to secondary_opts() or a list containing the following binary variables: cumulative, historic, primary_hist_additive, current, primary_current_additive. These parameters control the structure of the secondary model, see secondary_opts() for details.

delays

A call to delay_opts() defining delay distributions and options. See the documentation of delay_opts() and the examples below for details.

truncation

A call to trunc_opts() defining the truncation of the observed data. Defaults to trunc_opts(), i.e. no truncation. See the estimate_truncation() help file for an approach to estimating this from data where the dist list element returned by estimate_truncation() is used as the truncation argument here, thereby propagating the uncertainty in the estimate.

obs

A list of options as generated by obs_opts() defining the observation model. Defaults to obs_opts().

CrIs

Numeric vector of credible intervals to calculate.

backend

Character string indicating the backend to use for fitting stan models. Supported arguments are "rstan" (default) or "cmdstanr".

Details

In order to simulate, all parameters that are specified such as the mean and standard deviation of delays or observation scaling, must be fixed. Uncertain parameters are not allowed.

A function of the same name that was previously based on a reimplementation of that model in R with potentially time-varying scalings and delays is available as `convolve_and_scale()

Examples

# \donttest{
## load data.table to manipulate `example_confirmed` below
library(data.table)
cases <- as.data.table(example_confirmed)[, primary := confirm]
sim <- simulate_secondary(
  cases,
  delays = delay_opts(fix_parameters(example_reporting_delay)),
  obs = obs_opts(family = "poisson")
)
# }