generate_gold_standard() runs simulations in order to determine the gold standard of the simulations. gold_standard_default() is used to configure parameters pertaining this process.

generate_gold_standard(model)

gold_standard_default(
  tau = 30/3600,
  census_interval = 10/60,
  simulate_targets = FALSE
)

Arguments

model

A dyngen intermediary model for which the kinetics of the feature network has been generated with generate_kinetics().

tau

The time step of the ODE algorithm used to generate the gold standard.

census_interval

A granularity parameter of the gold standard time steps. Should be larger than or equal to tau.

simulate_targets

Also simulate the targets during the gold standard simulation

Value

A dyngen model.

See also

dyngen on how to run a complete dyngen simulation

Examples

model <- initialise_model( backbone = backbone_bifurcating(), gold_standard = gold_standard_default(tau = .01, census_interval = 1) ) # \donttest{ data("example_model") model <- example_model %>% generate_gold_standard()
#>
#> geom_path: Each group consists of only one observation. Do you need to adjust #> the group aesthetic?
# }