growth_sigmoid_prior: Create a Prior for the Sigmoid Growth Model

In maomlab/BayesPharma: Tools for Bayesian Analysis of Non-Linear Pharmacology Models

Create a Prior for the Sigmoid Growth Model

Description

Create a prior for the sigmoid growth model. If the function arguments K, K0, rate, lambda, or NULL, normal distribution priors will be set.

If you would like to set a parameter as a constant, enter a numeric value for the function argument.

For other distribution options, reference brms::prior and Prior Choice Recommendations

Usage

growth_sigmoid_prior(
  K = brms::prior(prior = normal(1, 0.5), nlpar = "K"),
  K0 = brms::prior(prior = normal(0, 0.5), nlpar = "K0"),
  rate = brms::prior(prior = normal(2, 0.5), nlpar = "rate", lb = 0),
  lambda = brms::prior(prior = normal(0.5, 0.5), nlpar = "lambda"),
  ...
)

Arguments

K	brms::brmsprior() or numeric. Prior for the K parameter. (Default: normal(1, 0.5))
K0	brms::brmsprior() or numeric. Prior for the K0 parameter. (Default: normal(0, 0.5))
rate	brms::brmsprior() or numeric. Prior for the rate parameter. (Default: normal(1, 1) with and a lower bound of 0).
lambda	brms::brmsprior() or numeric. Prior for the lambda parameter. (Default: normal(0.5, 0.5)).
...	additional brms::brmsprior() objects.

Value

brms::brmsprior() data.frame

Examples

## Not run: 
priors <- growth_sigmoid_prior(
  K = brms::prior(prior = normal(100, 20), nlpar = "K"),
  lambda = 1)

## End(Not run)

maomlab/BayesPharma documentation built on Aug. 24, 2024, 8:45 a.m.