TS_key_rmgarch: A simple multivariate GARCH-models from the...
In LAJordanger/localgaussSpec: Local Gaussian Spectral Analysis
View source: R/TS_key_dmt_rmgarch.R
TS_key_rmgarch R Documentation
A simple multivariate GARCH-models from the rmgarch-package.
Description
The TS_key_rmgarch-function is in essence a
wrapper around the cgarchsim-function from the
rmgarch-package, i.e. this is based on the
"Copula GARCH simulation". The key idea is that the user can
feed this wrapper the multivariate sample of interest (the
data-argument), and a specification of the univariate
GARCH-model, and then this function will take care of the rest.
Usage
TS_key_rmgarch(
n.sim = 100,
m.sim = 10,
uspec = NULL,
data = NULL,
rseed = NULL
)
Arguments
n.sim
The simulation horizon. Default value 100.
m.sim
The number of simulations. Default value 10.
uspec
The specification of the GARCH-model for the
univariate margins. Default value NULL. If this is not
specified, then ugarchspec from the
rugarch-package will be used to specify a trivial model.
data
The multivariate time series sample. The parameters of
interest for the multivariate GARCH-model will be extracted
from the model fitted to this sample.
rseed
Optional seeding value(s) for the random number
generator. This should be of length equal to m.sim.
Value
A multivariate GARCH-type time series is returned.
Note
This internal function has been added to the
TS_families-list, and its arguments should thus be given
to TS_sample, which will send them to this function by
the internal helper-function TS_sample_helper.
The rmgarch-package also contains other simulation
alternatives, but these have not been implemented. These
alternatives are 'dccsim' (Dynamical Conditional Correlation)
and 'gogarchsim' (Generalised Orthogonal).
LAJordanger/localgaussSpec documentation built on May 6, 2023, 4:31 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
View source: R/TS_key_dmt_rmgarch.R
| TS_key_rmgarch | R Documentation |
A simple multivariate GARCH-models from the rmgarch-package.
Description
The TS_key_rmgarch-function is in essence a
wrapper around the cgarchsim-function from the
rmgarch-package, i.e. this is based on the
"Copula GARCH simulation". The key idea is that the user can
feed this wrapper the multivariate sample of interest (the
data-argument), and a specification of the univariate
GARCH-model, and then this function will take care of the rest.
Usage
TS_key_rmgarch(
n.sim = 100,
m.sim = 10,
uspec = NULL,
data = NULL,
rseed = NULL
)
Arguments
n.sim |
The simulation horizon. Default value 100. |
m.sim |
The number of simulations. Default value 10. |
uspec |
The specification of the GARCH-model for the
univariate margins. Default value |
data |
The multivariate time series sample. The parameters of interest for the multivariate GARCH-model will be extracted from the model fitted to this sample. |
rseed |
Optional seeding value(s) for the random number generator. This should be of length equal to m.sim. |
Value
A multivariate GARCH-type time series is returned.
Note
This internal function has been added to the
TS_families-list, and its arguments should thus be given
to TS_sample, which will send them to this function by
the internal helper-function TS_sample_helper.
The rmgarch-package also contains other simulation
alternatives, but these have not been implemented. These
alternatives are 'dccsim' (Dynamical Conditional Correlation)
and 'gogarchsim' (Generalised Orthogonal).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.