Results from Approximate Bayesian Computation (ABC) calibration of an SIR network model fitted to Utah COVID-19 incidence data.
Format
A named list with the following elements:
- contact_rate
Posterior median of the contact rate.
- recovery_rate
Posterior median of the recovery rate.
- transmission_prob
Posterior median of the transmission probability.
- R0
Basic reproduction number computed from posterior medians.
- contact_rate_ci
95 percent credible interval for the contact rate.
- recovery_rate_ci
95 percent credible interval for the recovery rate.
- transmission_prob_ci
95 percent credible interval for the transmission probability.
- calibration_time_seconds
Total runtime of the ABC calibration (seconds).
- n_samples
Number of MCMC samples used in calibration.
- burnin
Number of burn-in iterations discarded.
- epsilon
ABC tolerance parameter.
- seed
Random seed used for reproducibility.
- posterior_samples
Matrix of post-burn-in accepted parameter samples.
- acceptance_rate
Acceptance rate of the ABC-MCMC algorithm (percent).
Examples
data("abc_calibration_params")
str(abc_calibration_params)
#> List of 14
#> $ contact_rate : num 1.18
#> $ recovery_rate : num 0.0937
#> $ transmission_prob : num 0.118
#> $ R0 : num 1.49
#> $ contact_rate_ci : Named num [1:2] 0.891 1.544
#> ..- attr(*, "names")= chr [1:2] "lower" "upper"
#> $ recovery_rate_ci : Named num [1:2] 0.0749 0.1496
#> ..- attr(*, "names")= chr [1:2] "lower" "upper"
#> $ transmission_prob_ci : Named num [1:2] 0.101 0.155
#> ..- attr(*, "names")= chr [1:2] "lower" "upper"
#> $ calibration_time_seconds: Named num 223
#> ..- attr(*, "names")= chr "elapsed"
#> $ n_samples : num 3000
#> $ burnin : num 1500
#> $ epsilon : num 10
#> $ seed : num 122
#> $ posterior_samples : num [1:1500, 1:3] 1.49 1.49 1.55 1.57 1.57 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:1500] "[1501,]" "[1502,]" "[1503,]" "[1504,]" ...
#> .. ..$ : NULL
#> $ acceptance_rate : num 100