Calculate estimated individual COI with uncertainty — calculate_individual

Returns per-host complexity of infection (COI). With use_map = TRUE you get a point estimate (MAP); with use_map = FALSE and MCMC samples, posterior mean, SD, and credible interval are computed.

Usage

calculate_individual_coi(
  results,
  use_map = TRUE,
  n_samples = 100,
  interval = 0.95
)

Arguments

results: A snp_slice_results object.
use_map: If TRUE (default), use MAP only; uncertainty columns are NA. If FALSE, use MCMC samples for mean, SD, and interval.
n_samples: When use_map = FALSE, number of MCMC samples to use (capped at available post-burnin samples).
interval: Numeric in (0, 1). Credible interval width when using MCMC (e.g. 0.95 for 2.5 and 97.5 percent quantiles).

Value

A data frame with one row per host: host_index, host_id, coi_estimate, coi_sd, coi_lower, coi_upper. Uncertainty columns are NA when using MAP or when no MCMC samples are available.

Examples

result <- load_example_results()
coi_map <- calculate_individual_coi(result, use_map = TRUE)
head(coi_map)
#>   host_index    host_id coi_estimate coi_sd coi_lower coi_upper
#> 1          1 specimen_1            1     NA        NA        NA
#> 2          2 specimen_2            1     NA        NA        NA
#> 3          3 specimen_3            1     NA        NA        NA
#> 4          4 specimen_4            1     NA        NA        NA
#> 5          5 specimen_5            1     NA        NA        NA
#> 6          6 specimen_6            1     NA        NA        NA
if (!is.null(result$mcmc_samples)) {
  coi_post <- calculate_individual_coi(result, use_map = FALSE, n_samples = 50)
  head(coi_post)
}
#>   host_index    host_id coi_estimate coi_sd coi_lower coi_upper
#> 1          1 specimen_1            1      0         1         1
#> 2          2 specimen_2            1      0         1         1
#> 3          3 specimen_3            1      0         1         1
#> 4          4 specimen_4            1      0         1         1
#> 5          5 specimen_5            1      0         1         1
#> 6          6 specimen_6            1      0         1         1