simulate_cougher: Generate a simulated cough timeline for a user
In hyfe-ai/hyfer: R Utilities for Interacting with Hyfe Data

Simulate an hourly cough timeseries for an imaginary user.

simulate_cougher(
  rate_mean,
  rate_variance = NULL,
  hours = 24 * 30,
  start_timestamp = as.numeric(Sys.time()),
  tz = Sys.timezone(),
  distribution = "nb",
  format_time = TRUE,
  random_seed = NULL
)

`rate_mean`	Mean hourly cough rate
`rate_variance`	Variance in the hourly cough rate. If left `NULL`, variance will be estimated using one of Hyfe's standard regression models, which should produce realistic results for any scenario.
`hours`	Duration of time series, in hours. Default is 720 (about a month).
`start_timestamp`	Optional start timestamp (seconds since midnight UTC on January 1, 1970). Default is to use your system's current time.
`tz`	Optional timezone for timestamp. Default is your system timezone.
`distribution`	The frequency distribution to base the simulation upon. Default is `'nb'`, negative binomial. This is currently the only option.
`format_time`	If `TRUE` (the default), formatted date/time variables will be returned using `format_hyfe_time()`. It may be useful to change this to `FALSE` if conducting iterative analyses that rely on speed.
`random_seed`	Set the random number generator seed in order to replicate a cougher.

A dataframe with a timestamp column, a coughs column, and a dummy rec column in which all rows have 1 full hour of "recording". If format_time is TRUE, additional date/time variables are provided. See format_hyfe_time() or (this section of the vignette)https://hyfe-ai.github.io/hyfer/#hyfetime.