AIC: Akaike information criterion (AIC).

Description Usage Arguments Details Value References Examples

View source: R/AIC.R

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

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AIC(fit)

## S3 method for class 'MSGARCH_ML_FIT'
AIC(fit)

## S3 method for class 'MSGARCH_MCMC_FIT'
AIC(fit)

Arguments

fit

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

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.

Value

AIC value.

References

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

Examples

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# 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)

MSGARCH documentation built on Sept. 14, 2017, 5:03 p.m.