DIC and CPO

Generic front doors onto the two criteria tulpa_criteria() computes that the loo package owns no generic for. WAIC and PSIS-LOO have theirs (loo::waic(), loo::loo()), so a model package registers methods on those rather than on new names that would mask them.

Usage

dic(object, ...)

# Default S3 method
dic(object, loglik_at_mean = NULL, ...)

cpo(object, ...)

# Default S3 method
cpo(object, ...)

Arguments

object

A pointwise log-likelihood matrix (draws x observations), or a fitted model object a method is registered for.

...

Passed to tulpa_criteria() (e.g. group, chunk_size).

loglik_at_mean

Length-n_obs vector of pointwise log-likelihoods at the posterior mean of the parameters. Required for DIC's plug-in deviance; without it the DIC fields are NA.

Value

A tulpa_criteria object.

Details

The default methods take a draws x observations pointwise log-likelihood matrix, the same input tulpa_criteria() takes. A model package registers a method taking its own fit object, builds the matrix from the posterior, and delegates here.

See also

tulpa_criteria() for every criterion at once and for what the LOO unit means.

Examples

set.seed(1)
y  <- rnorm(40)
mu <- matrix(rnorm(200 * 40, sd = 0.2), 200, 40)
ll <- dnorm(matrix(y, 200, 40, byrow = TRUE), mean = mu, log = TRUE)
cpo(ll)