Generate an R_t timeseries simulation based on a small set of fixed time points.

Generate an R_t timeseries simulation based on a small set of fixed time points.

generateRt(
  name,
  dateAtTime0 = "2020-01-01",
  length = 365,
  breaks = sort(c(0, sample(0:364, 5))),
  R_t = alternatingRandom(fn = rlnorm),
  smooth = TRUE,
  sawtooth = FALSE,
  Gt.mean = 5,
  Gt.sd = 4,
  ...
)

Arguments

name	- a meaningful name for this growth rate scenario
dateAtTime0	- the date at time zero
length	- how many days in the scenario
breaks	- time points (between 0 and length) when the growth rate is at a set value.
R_t	- the values of the reproduction at the time points up to and including the break points, optionally an additional point for the period to the end of the time-series
smooth	- should the rates be interpolated with a spline. If so it may be a good ideal to specify the growth rate at zero.
sawtooth	- if the rates are not smooth should they be a step function or a saw-tooth linear function.
Gt.mean	- mean of the generation time for conversion to R_t
Gt.sd	- sd of the generation time for conversion to R_t
...	- ignored

Value

- a list containing name - the scenario name, ts - a tibble with the date, generated growth rate and R_t values, events - the time-points of the period, infectivityProfile - an infectivity_profile