plot incidence and counterfactual scenario — hom_plot_counterfactual_by

on same plot show counterfactual and incidence posterior predictive distributions across time and faceted by location. Shaded regions represent the 50 draws shown as lines.

hom_plot_counterfactual_by_location(
  fit,
  outbreak_cases = NULL,
  location_labels = NULL
)

Arguments

fit	output of [seir_model_fit]
outbreak_cases	matrix of outbreak case data
location_labels	tibble with columns `site` and `location`. Will be used to relabel numeric location to values in `site` column

Value

list containing: * plot - ggplot object * table - tibble object of results * violin_plot - ggplot object

Note

Naming convention throughout is snake case with prefix "hom_" to denote Hierarcical Outbreak Model

Examples

if (FALSE) {
 tmax <- 5
 pop_size <- 100
 dim(pop_size) <- c(1)
 example_incidence <- matrix(c(1,1,2,3,2),ncol=1)
 fit <- seir_model_fit(tmax,1,example_incidence,pop_size)
 result <- hom_plot_incidence_by_location(fit)
 # plot results
 show(result$plot)
 }