simulate_outbreak: Simulate the process of flipping until failure for K clusters
In skgallagher/TBornotTB: Analyze Tuberculosis Patients in Maryland

Description Usage Arguments Details Value Examples

Simulate the process of flipping until failure for K clusters

simulate_outbreak(
  K,
  inf_params,
  smear_pos_prob,
  max_size = 50,
  start_at_outsider = FALSE,
  keep_zero_clusters = FALSE,
  sample_covariates = NULL
)

`K`	number of total clusters to simulate
`inf_params`	vector with beta_0 and beta_1
`smear_pos_prob`	probability of a smear positsive
`max_size`	maximum size a cluster can be
`start_at_outsider`	if TRUE, we start at an unobserved outsider instead of a single index case
`keep_zero_clusters`	Do I keep track of the the cluster consisting only of the unobserved root node? Default is FALSE.
`sample_covariates`	used for multi-variate people

breadth not depth. Generate generation by generation as opposed to going up the branch til termination.

data frame with the following columns

cluster_id: unique cluster ID
person_id: order of infection in the cluster
smear: - 1 (negative) / + 1 (positive)
gen: generation number (>=0)
inf_id: ID of the infector
n_inf: number of people infected by person
cluster_pos: number of positive smears in the cluster
cluster_size: number in cluster
censored: whether the cluster end was censored or not

inf_params <- c("beta_0" = -2, "beta_1" = 1)
smear_pos_prob <- .8
max_size <- 30
K <- 5
out <- simulate_outbreak(K = K,
                                inf_params = inf_params,
                                smear_pos_prob = smear_pos_prob,
                                max_size = max_size)