This function calculates the log-likelihood value or deviance (twice the
negative log-likelihood) for I-prior models. It works for both
ipriorMod and ipriorKernel class objects.
# S3 method for ipriorMod
logLik(object, theta = NULL, ...)# S3 method for ipriorMod
deviance(object, theta = NULL, ...)
# S3 method for ipriorKernel
logLik(object, theta = NULL, ...)
# S3 method for ipriorKernel
deviance(object, theta = NULL, ...)
An object of class ipriorMod or ipriorKernel.
(Optional) Evaluates the log-likelihood at theta.
Not used.
For ipriorKernel objects, the log-likelihood or deviance is calculated
at the default parameter values: scale parameters and error precision are
equal to one, while hyperparameters of the kernels (e.g. Hurst index,
lengthscale, etc.) are the default values (see here for
details) or ones that has been specified. For ipriorMod objects, the
log-likelihood or deviance is calculated at the last obtained value from the
estimation method.
For both types of objects, it is possible to supply parameter values at which
to calculate the log-likelihood/deviance. This makes estimating an I-prior
model more flexible, by first loading the variables into an
ipriorKernel object, and then using an optimiser such as
optim. Parameters have been transformed so that they can
be optimised unconstrained.
check_theta.