Compute the smallest index at which joint estimation should start

Source: R/gibbs_draws.R

Unless specified by the user, t_min in estimate_advantage() is computed as the sum of two indices:

compute_t_min(incid, si_distr, miss_at_most)

Arguments

incid

a multidimensional array containing values of the incidence for each time step (1st dimension), location (2nd dimension) and pathogen/strain/variant (3rd dimension)

si_distr

a matrix with two columns, each containing the probability mass function for the discrete serial interval for each of the two pathogen/strain/variants, starting with the probability mass function for day 0 in the first row, which should be 0. Each column in the matrix should sum to 1.

miss_at_most

numeric. Probability mass in the tail of the SI distribution

Value

integer

Details

  • the first day of non-zero incidence across all locations, computed using first_nonzero_incid()

  • the 95th percentile of the probability mass function of the SI distribution across all variants computed using compute_si_cutoff()

Author

Sangeeta Bhatia