BIC.gamBiCop

BIC,gamBiCop-method

Function calculating the Schwarz's Bayesian Information Criterion (BIC)
for an object of the class
<code>gamBiCop</code> (note that the models are
usually fitted by penalized likelihood maximization).

Implementation of various inference and simulation tools to
apply generalized additive models to bivariate dependence structures and
non-simplified vine copulas.

Thibault Vatter

gamCopula

Generalized Additive Models for Bivariate Conditional Dependence
Structures and Vine Copulas

Thomas Nagler

BIC.gamBiCop function

<dl><dt>object</dt>
<dd>An object of the class
<code>gamBiCop</code>.</dd>
<dt>...</dt>
<dd>un-used in this class</dd></dl>

Arguments

Schwarz's Bayesian Information Criterion for a gamBiCop Object — BIC.gamBiCop

<dl>

<dt>object</dt>
<dd>An object of the class
<code>gamBiCop</code>.</dd>


<dt>...</dt>
<dd>un-used in this class</dd>

</dl>

BIC.gamBiCop: Schwarz's Bayesian Information Criterion for a gamBiCop Object

Description

Usage

Value

Arguments

See Also