Update certain components of DualEndpoint model with regard to prior variance factor of the random walk.

A simple helper function that takes DualEndpoint object and updates priormodel, modelspecs, init, sample slots according to the random walk variance.

Usage

h_model_dual_endpoint_sigma2betaW(use_fixed, sigma2betaW, de)

Arguments

use_fixed

(flag)
indicates whether a fixed value for sigma2betaW should be used or not. If sigma2betaW is not supposed to be a fixed value, a prior distribution from the Inverse-Gamma distribution will be used. See the details below, under sigma2betaW argument.

sigma2betaW

(numeric)
the prior variance factor of the random walk prior for the biomarker model. Either a fixed value or Inverse-Gamma distribution parameters, i.e. vector with two elements named a and b.

de

(DualEnpoint)
dual endpoint model whose slots will be updated.

Value

A DualEndpoint model with updated priormodel, modelspecs, init, sample slots.

See also

DualEndpointRW.