Description Usage Arguments Details See Also

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.

1 2 3 4 5 6 7 8 9 10 11 |

`object` |
An object of class |

`theta` |
(Optional) Evaluates the log-likelihood at |

`...` |
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.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.