Description Usage Arguments Examples
View source: R/generate_configuration.R
This function generates a list of settings to be used as configuration
in run_mcmc()
. If nothing is supplied, default settings are returned.
1 2 3 |
n_iter |
total number of iterations including burnin. The default value is 30000. |
n_burnin |
number of interations in burnin. The default value is 10000 or one third of the supplied value for n_iter. During the burnin, the proposal widths are updated to optimise acceptance ratios. The chains returned by run_mcmc include the burnin. |
set_seed |
logical; if TRUE (default) a seed is set at the beginning of the MCMC iterations to ensure reproducibility of the chain. |
store_params |
if STORE_ALL (default) all iterations of the chains of the parameters are returned. If a number k is supplied, only every k-th iteration is stored. k = 1 is the same as STORE_ALL. |
store_statuses |
if STORE_ALL (default) for each patient and each iteration the colonisation time is returned. If a number k is supplied, only every k-th iteration is stored. If AGGREGATED only aggregated (total number of susceptible, acquired, imported) patient data is returned. k = 1 is the same as STORE_ALL. |
infer_covariate_effects |
if c("b","s","r") (default) covariate effects on transmissibility (b), susceptibility (s) and test sensitivity (r) are inferred. If NONE, no covariate effects are inferred and the values of b, s and r are set to 1. If a vector containing any of the covariate effects parameter b, s and r is supplied, effects on these parameters only are inferred and the remaining parameters are set to 1. |
1 2 3 4 5 6 7 8 | ## use default configuration
generate_configuration()
## modify number of iterations
generate_configuration(n_iter = 1000, n_burnin = 300)
## infer effect of covariates on susceptibility only
generate_configuration(infer_covariate_effects = c("s"))
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