dmbc (version 0.4.0)

dmbc_prior: Auxiliary Function for Setting DMBC Model Priors

Description

dmbc_prior() is an auxiliary function as user interface for dmbc() fitting. Typically only used when calling the dmbc() function. It is used to set prior hyperparameters.

prior_dmbc() is an alias for dmbc_prior().

check_prior() is an auxiliary function that verifies the correctness of the prior hyperparameters provided before a DMBC is fitted with dmbc().

update_prior() is an auxiliary function to modify a set of prior choices using a new value of p and G. It is intended for internal use mainly in the dmbc_ic() function.

Usage

dmbc_prior(
  eta = list(a = rep(1.5, .dmbcEnv$current_G), b = rep(0.5, .dmbcEnv$current_G)),
  sigma2 = list(a = 0.1, b = 0.1),
  lambda = rep(1, .dmbcEnv$current_G)
)
prior_dmbc(
  eta = list(a = rep(1.5, .dmbcEnv$current_G), b = rep(0.5, .dmbcEnv$current_G)),
  sigma2 = list(a = 0.1, b = 0.1),
  lambda = rep(1, .dmbcEnv$current_G)
)
check_prior(prior)
update_prior(prior, p, G)

Arguments

eta

A named list containing the hyperparameters for the prior distribution of the ${\eta }_1,\dots ,{\eta }_G$ parameters. It should contain two numeric vectors, namely a and b.

sigma2

A named list containing the hyperparameters for the prior distributions of the ${\sigma }_1^2,\dots ,{\sigma }_G^2$ parameters. It should contain two numeric scalars, namely a and b.

lambda

A list containing the hyperparameters for the prior distribution of the ${\lambda }_1,\dots ,{\lambda }_G$ parameters. It should contain a single numeric vector.

prior

A named list of prior hyperparameters.

p

A length-one numeric vector indicating the number of dimensions of the latent space.

G

A length-one numeric vector indicating the number of cluster to partition the S subjects.

Value

A list with the prior hyperparameters as components.

See Also

dmbc()

Examples

# NOT RUN {
data(simdiss, package = "dmbc")
# Shorter run than default.
sim.fit <- dmbc(simdiss,
  control = dmbc_control(burnin = 1000, nsim = 2000, thin = 1, verbose = TRUE),
  prior = dmbc_prior(sigma2 = list(a = 1, b = 4)))
# }
# NOT RUN {
# }