ExponentialTransitionPriors: Build an exponential TransitionPriors object, which governs...

In grantbrown/ABSEIR: Posterior Approximation to Fully Bayesian Spatial SEIR Models Using Multithreaded C++

Description

Build an exponential TransitionPriors object, which governs how individuals move from the exposed to infectious and infectious to removed compartments.

Usage

ExponentialTransitionPriors(p_ei, p_ir, p_ei_ess, p_ir_ess)

Arguments

p_ei	the estimated probability that, at a given time point, an exposed individual becomes infectious.
p_ir	the estimated probability that, at a given time point, an infectious individual is removed from the population.
p_ei_ess	the effective sample size, or corresponding number of observations of the E to I process, associated with p_ei
p_ir_ess	the effective sample size, or corresponding number of observations of the I to R process, associated with p_ir

Details

ExponentialTransitionPriors provides the parameterization from Brown et al. 2015, which employs a constant transition probability over discrete time, corresponding to a geometric compartment membership time. For additional discussion, see Brown et al. 2015.

See Also

TransitionPriors, PathSpecificTransitionPriors, WeibullTransitionPriors

Examples

transitionPriors <- ExponentialTransitionPriors(1/5,1/7, 100, 100)

grantbrown/ABSEIR documentation built on Oct. 14, 2021, 2:32 p.m.