Generate a multinomial outbreak defined by per class growth rates and a poisson model

Generate a multinomial outbreak defined by per class growth rates and a poisson model

Usage

sim_multinomial(
  changes = tibble::tibble(t = c(0, 20, 40, 60, 80), variant1 = c(0.1, 0, -0.1, 0, 0.1),
    variant2 = c(0.15, 0.05, -0.05, -0.01, 0.05), variant3 = c(0, 0.05, -0.05, +0.05,
    -0.05), ),
  initial = c(100, 100, 100),
  time_unit = "1 day",
  ...
)

Arguments

changes

a list of time points in column t and growth rates per week per class, in other columns.

initial

the size of the initial outbreak per class. There should be one entry per class

time_unit

e.g. a daily or weekly time series: "1 day", "7 days"

...

Named arguments passed on to sim_poisson_model

fn_imports

a function that takes input vector t and returns the number of imported cases at times t.

seed

a random seed

kappa

a dispersion parameter. 1 is no dispersion (compared to poisson), smaller values mean more dispersion.

max_time

the desired length of the time series,

fn_growth

a function that takes input vector t and returns the growth rates at times t

Value

a case count time series including class, count and time columns

Examples

if (interactive()) {
  plot_counts(
    sim_multinomial() %>% dplyr::glimpse()
  )
}