This function computes the DIC (deviance information criterion) for the estimated model in a fusion object.
Usage
dic(x)
Arguments
x
an object of class fusion
Value
The DIC for the estimated model in the fusion object.
Details
The DIC can be easily computed from the MCMC output and is defined as
\(DIC = 2 \overline{D(\theta)} - D(\overline{\theta})\), where \(\overline{D(\theta)} =
\frac{1}{M} \sum \limits_{m=1}^{M} D(\theta^{(m)})\) is the average posterior deviance and
\(D(\bar{\theta})\) is the deviance evaluated at \(\bar{\theta} = \frac{1}{M} \sum
\limits_{m=1}^{M} \theta^{(m)}\). \(\theta^{(m)}\) are samples from the posterior of the model
and M is the number of MCMC iterations.
References
Spiegelhalter, D., Best, N., Carlin, B., and van der Linde, A. (2002). Bayesian Measures of Model
Complexity and Fit. J. R. Statist. Soc. B, 64(4), 583-639. 10.1111/1467-9868.00353