Construct priors for the biomarker model.

The biokinetics model has 6 parameters: t0, tp, ts, m1, m2, m3 corresponding to critical time points and gradients. See the model vignette for details: vignette("model", package = "epikinetics"). Each of these parameters has a Gaussian prior, and these can be specified by the user. This function takes means and standard deviations for each prior and constructs an object of type 'biokinetics_priors' to be passed to the model.

biokinetics_priors(
  mu_values = c(4, 10, 60, 0.25, -0.02, 0),
  sigma_values = c(2, 2, 3, 0.01, 0.01, 0.01)
)

Arguments

mu_values

Mean of Gaussian prior for each of t0, tp, ts, m1, m2, m3, in order.

sigma_values

Standard deviation of Gaussian prior for each of t0, tp, ts, m1, m2, m3, in order.

Value

A named list of type 'biokinetics_priors'.

Examples

priors <- biokinetics_priors(mu_values = c(4.0, 10, 60, 0.25, -0.02, 0),
sigma_values = c(2.0, 2.0, 3.0, 0.01, 0.01, 0.01))