Deviance of a fitted gllvmTMB model

-2 * logLik(object), delegating through logLik.gllvmTMB_multi() rather than recomputing anything independently. This is deliberate: on a penalised (ridged) fit – aghq_ridge set to a finite value – logLik() already discloses, with a warning, that the returned value is the unpenalised log-likelihood evaluated AT a penalised MAP point, not at its own maximum. Because deviance() is defined purely in terms of logLik() here, that same disclosure fires exactly once and is not repeated or re-derived.

Usage

# S3 method for class 'gllvmTMB_multi'
deviance(object, ...)

Arguments

object

A fit returned by gllvmTMB().

...

Currently unused.

Value

A single numeric value, -2 * as.numeric(logLik(object)). On a ridged fit this carries the same MAP-point caveat as logLik(): the value is -2 times the unpenalised likelihood at the penalised estimate, not at its own maximum, and the warning issued by logLik() is inherited unchanged.