DIC {extrememix} | R Documentation |
Deviance Information Criterion
Description
Computation of the DIC for an extreme value mixture model
Usage
DIC(x, ...)
## S3 method for class 'evmm'
DIC(x, ...)
Arguments
x |
the output of a model estimated with |
... |
additional arguments for compatibility. |
Details
Let y
denote a dataset and p(y|\theta)
the likelihood of a parametric model with parameter \theta
. The deviance is defined as D(\theta)= -2\log p(y|\theta)
. The deviance information criterion (DIC) is defined as
DIC = D(\hat\theta) + 2p_D,
where \hat\theta
is the posterior estimate of \theta
and p_D
is referred to as the effective number of parameters and defined as
E_{\theta|y}(D(\theta)) - D(\hat\theta).
Models with a smaller DIC are favored.
Value
The DIC of a model estimated with extrememix
References
Spiegelhalter, David J., et al. "Bayesian measures of model complexity and fit." Journal of the Royal Statistical Society: Series B 64.4 (2002): 583-639.
See Also
Examples
DIC(rainfall_ggpd)