Poisson model for incidence data

Usage

poisson_gam_model.incidence(
  d = i_incidence_input,
  model_fn = gam_poisson_model_fn(...),
  ...,
  frequency = "1 day",
  predict = list(),
  ip = i_discrete_ip,
  quick = FALSE,
  .progress = interactive()
)

Arguments

model_fn: a function that takes data relating to one time series (e.g. the input data d on a group by group basis) and returns a fitted GAM. The default creates a simple poisson model based on count alone (gam_poisson_model_fn()).
predict: if the GAM model in model_fn introduces other variables we need to know what their values should be fixed at for prediction. This is a named list of defaults for variables in the model supplied by model_fn. These defaults will be used in prediction. This may be supplied as part of the model function generator ( e.g. gam_delayed_reporting(...)$predict). If this is set to exactly FALSE no prediction is performed and a list column of fitted GAM models returned instead.