Configure the model fitting — set_fit

Sets model fitting options in EpiSewer.

Usage

set_fit_opts(sampler = sampler_stan_mcmc(), model = model_stan_opts())

Arguments

sampler: Which type of sampler should be used for model fitting? Currently, only sampler_stan_mcmc() is supported.
model: Details about the model file to be used, see model_stan_opts(). This also makes it possible for users to supply customized models.
results: Details about the results to be returned, see set_results_opts(). For example, what credible intervals to use for summarizing posterior distributions or whether to return the fitted model object.

Value

A list with the model fitting options.

Examples

ww_data <- ww_data_SARS_CoV_2_Zurich
ww_assumptions <- ww_assumptions_SARS_CoV_2_Zurich

ww_fit_opts <- set_fit_opts(
  sampler = sampler_stan_mcmc(
    chains = 2,
    parallel_chains = 2,
    iter_warmup = 400,
    iter_sampling = 400,
    seed = 42 # ensures reproducibility
  )
)

ww_results_opts <- set_results_opts(
  fitted = TRUE, # return full model fit
  summary_intervals = c(0.5, 0.8, 0.95),
  samples_ndraws = 100
)

if (FALSE) ww_result <- EpiSewer(
  data = ww_data,
  assumptions = ww_assumptions,
  fit_opts = ww_fit_opts,
  results_opts = ww_results_opts
) # \dontrun{}