This function calculates the log-likelihood value or deviance (twice the
negative log-likelihood) for I-prior models. It works for both
ipriorKernel class objects.
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An object of class
(Optional) Evaluates the log-likelihood at
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
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.
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