Volatility | R Documentation |
Method returning the in-sample conditional volatility.
Volatility(object, ...) ## S3 method for class 'MSGARCH_SPEC' Volatility(object, par, data, ...) ## S3 method for class 'MSGARCH_ML_FIT' Volatility(object, newdata = NULL, ...) ## S3 method for class 'MSGARCH_MCMC_FIT' Volatility(object, newdata = NULL, ...)
object |
Model specification of class |
... |
Not used. Other arguments to |
par |
Vector (of size d) or matrix (of size |
data |
Vector (of size T) of observations. |
newdata |
Vector (of size T*) of new observations. (Default |
If a matrix of MCMC posterior draws is given, the Bayesian predictive conditional volatility is calculated.
In-sample condititional volatility (vector of size T + T*) of class MSGARCH_CONDVOL
.
The MSGARCH_CONDVOL
class contains the plot
method.
# create specification spec <- CreateSpec() # load data data("SMI", package = "MSGARCH") # in-sample volatility from specification par <- c(0.1, 0.1, 0.8, 0.2, 0.1, 0.8, 0.99, 0.01) vol <- Volatility(object = spec, par = par, data = SMI) head(vol) plot(vol) # in-sample volatility from ML fit fit <- FitML(spec = spec, data = SMI) vol <- Volatility(object = fit) head(vol) plot(vol) ## Not run: # in-sample volatility from MCMC fit set.seed(1234) fit <- FitMCMC(spec = spec, data = SMI) vol <- Volatility(object = fit) head(vol) plot(vol) ## End(Not run)
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