MSGARCH (version 1.3)

AIC: Akaike information criterion (AIC).

Description

Method which computes the Akaike information criterion (AIC) from a fit object of type MSGARCH_ML_FIT created with FitML or MSGARCH_MCMC_FIT created with FitMCMC.

Usage

AIC(fit)
# S3 method for MSGARCH_ML_FIT
AIC(fit)
# S3 method for MSGARCH_MCMC_FIT
AIC(fit)

Arguments

fit

Fit object of type MSGARCH_ML_FIT created with FitML or MSGARCH_MCMC_FIT created with FitMCMC.

Value

AIC value.

Details

Computes the Akaike information criterion (AIC) based on the work of Akaike (Akaike, 1974). If a matrix of MCMC posterior draws is given, the AIC on the posterior mean is calculated.

References

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716-723.

Examples

# NOT RUN {
# load data
data("SMI", package = "MSGARCH")

# create model specification
# MS(2)-GARCH(1,1)-Normal (default)
spec <- CreateSpec()

# fit the model on data by ML
fit <- FitML(spec = spec, data = SMI)

# compute AIC
AIC(fit)
# }