GAS (version 0.3.3)

MultiGASSpec: Multivariate GAS specification

Description

Specify the conditional distribution, scaling mechanism and time-varying parameters for multivariate GAS models.

Usage

MultiGASSpec(Dist = "mvnorm", ScalingType = "Identity",
             GASPar = list(location = FALSE, scale = TRUE,
                           correlation = FALSE, shape = FALSE),
             ScalarParameters = TRUE)

Arguments

Dist

character indicating the label of the conditional distribution. Available distribution can be displayed using the function DistInfo. Default value Dist = "mvnorm"

ScalingType

character indicating the scaling mechanism for the conditional score. Only ScalingType = "Identity" is supported for multivariate distributions.

GASPar

list containing information about which parameters of the conditional distribution have to be time-varying. location = TRUE refers to the location parameters, scale = TRUE refers to the scale parameters, shape = TRUE refers to the shape parameter (e.g., the degree of freedom of the multivariate Student-t distribution), correlation = TRUE refers to the correlations. If the distribution specified in the Dist argument does not have, say, a shape parameter, the condition shape = TRUE is ignored.

ScalarParameters

logical indicating if the parameters of the locations, scales and correlations dynamic have to be scalars or a diagonal matrices. By default ScalarParameters = TRUE.

Value

An object of the class mGASSpec

Details

All the information regarding the supported multivariate conditional distributions can be investigated using the DistInfo function.

References

Creal D, Koopman SJ, Lucas A (2011). "A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations." Journal of Business & Economic Statistics, 29(4), 552-563. 10.1198/jbes.2011.10070.

Creal D, Koopman SJ, Lucas A (2013). "Generalized Autoregressive Score Models with Applications." Journal of Applied Econometrics, 28(5), 777-795. 10.1002/jae.1279.

Harvey AC (2013). Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series. Cambridge University Press.

Examples

# NOT RUN {
# Specify a GAS model with multivariate Student-t
# conditional distribution and time-varying locations,
# scales and correlations  parameters but constant shape parameter.

library("GAS")

GASSpec = MultiGASSpec(Dist = "mvt", ScalingType = "Identity",
                       GASPar = list(location = TRUE, scale = TRUE,
                                     correlation = TRUE, shape = FALSE))

GASSpec

# }