garchSpec {fGarch} | R Documentation |
Specifies an univariate GARCH time series model.
garchSpec(model = list(omega = 1.0e-6, alpha = 0.1, beta = 0.8), presample = NULL, cond.dist = c("rnorm", "rged", "rstd", "rsnorm", "rsged", "rsstd"), rseed = NULL) show.garchSpec(object)
cond.dist |
a character string naming the desired conditional distribution.
Valid values are "dnorm" , "dged" , "dstd" ,
"dsnorm" , "dsged" , "dsstd" . The default value
is the normal distribution.
|
model |
a list of GARCH model parameters: omega - the constant coefficient of the variance equation,
by default 1e-6; alpha - the value or vector of autoregressive coefficients,
by default 0.1, specifying a model of order 1; beta - the value or vector of variance coefficients,
by default 0.8, specifying a model of order 1;
The optional values for the linear part are: mu - the mean value, by default 0; ar - the autoregressive ARMA coefficients, by default 0; ma - the moving average ARMA coefficients, by default 0.
The optional parameters for the conditional distributions are: skew - the skewness parameter (also named xi), by default
0.9, effective only for the "dsnorm" , the "dsged" ,
and the "dsstd" skewed conditional distributions; shape = the shape parameter (also named nu), by default 2
for the "dged" and "dsged" , and by default 4
for the "dstd" and "dsstd" conditional
distributions.Note, the default model specifies Bollerslev's GARCH(1,1) model with normal distributed innovations. |
object |
an object of class garchSpec as returned from the function
garchSpec() .
|
presample |
a numeric three column matrix with start values for the series, for the innovations, and for the conditional variances. For an ARMA(m,n)-GARCH(p,q) process the number of rows must be at least max(m,n,p,q), longer presamples are cutted. |
rseed |
single integer argument, the seed for the intitialization of the random number generator for the innovations. |
garchSpec
returns a S4 object of class garchSpec
with the following slots:
@call |
the call of the garch function.
|
@formula |
a list with two formula entries for the mean and variance equation. |
@model |
a list with the model parameters. |
@presample |
a numeric matrix with presample values. |
@distribution |
a character string with the name of the conditional distribution. |
@rseed |
an integer with the random number generator seed. |
Diethelm Wuertz for the Rmetrics R-port.
## garchSpec - # Normal Conditional Distribution: spec = garchSpec() spec # Skewed Normal Conditional Distribution: spec = garchSpec(model = list(skew = 0.8), cond.dist = "rsnorm") spec # Skewed GED Conditional Distribution: spec = garchSpec(model = list(skew = 0.9, shape = 4.8), cond.dist = "rsged") spec