define_abc_prms: Define parameters for Appoximate Bayesian Computation (ABC)...

In phac-nml-phrsd/wem: Wastewater Epidemic Model

Define parameters for Appoximate Bayesian Computation (ABC) fitting method.

Description

Determine the required parameters (iteration, acceptance and weight) for the ABC fitting process. The weights specify the importance of different data sources utilized simultaneously in the fitting process. There are three data sources for simultaneous fitting: reported cases, viral concentration in wastewater and hospitalization (admission or occupancy).

Usage

define_abc_prms(iter, accept, case.weight, ww.weight, hosp.weight, hosp.type)

Arguments

iter	Numeric. Number of prior iterations for ABC fitting.
accept	Numeric. Acceptance ratio (so the number of posterior samples is iter * accept).
case.weight	Numeric, float. Relative weight for clinical cases
ww.weight	Numeric, float. Relative weigth for viral concentration in wastewater.
hosp.weight	Numeric, float. Relative weight for hospitalization.
hosp.type	String. Type of hospitalization data: "hosp.adm" for hospital admissions, "hosp.occ" for hospital occupancy and NULL for no hospital data.

Value

Nested list of ABC parameters.

See Also

define_fit_priors(), fit()

Examples

prm.abc = define_abc_prms(
iter        = 1e4,
accept      = 1e-2,
case.weight = 1.0,
ww.weight   = 2.5,
hosp.weight = 1.0,
hosp.type   = 'hosp.adm')

phac-nml-phrsd/wem documentation built on June 6, 2024, 11:06 p.m.