set_user_prior: Set a user-defined prior

Description

Constructs a user-defined prior distribution for use as the argument prior in hef or hanova1.

Usage

set_user_prior(prior, ..., model = c("beta_binom", "gamma_pois", "anova1"),
  anova_d = 2)

Arguments

prior

An R function returning the log of the prior density for of (perhaps a subset of) the hyperparameter vector \(\phi\).

...

Further arguments giving the names and values of any parameters involved in the function prior.

model

A character string. Abbreviated name of the model: "beta_binom" for beta-binomial, "gamma_pois" for gamma-Poisson, "anova1" for 1-way ANOVA.

anova_d

An integer scalar. Only relevant if model = anova1. If anova_d = 2 then prior must return the log-prior density for the standard deviations \((\sigma_\alpha, \sigma)\) and a normal prior with mean mu0 and standard deviation sigma0 is used for \(\mu\). The values of mu0 = 0 and sigma0 = Inf are set in the call to hanova1, with default values mu0 = 0 and sigma0 = Inf. If anova_d = 3 then prior must return the log-prior density for \((\mu, \sigma_\alpha, \sigma)\).

Value

A list of class "bang_prior". Will contain the component prior, the user-supplied function to evaluate the log of the prior, and any arguments supplied in ....

Details

For details of the hyperparameters in \(\phi\) see the Details section of hef for the models beta_binom and gamma_pois and of hanova1 for the model anova1.

Examples

Run this code

# NOT RUN {
# User-defined prior, passing parameters
# (equivalent to prior = "gamma" with hpars = c(1, 0.01, 1, 0.01))
user_prior <- function(x, hpars) {
  return(dexp(x[1], hpars[1], log = TRUE) + dexp(x[2], hpars[2], log = TRUE))
}
user_prior_fn <- set_user_prior(user_prior, hpars = c(0.01, 0.01))
# }