public class GARCH
extends java.lang.Object
implements java.io.Serializable
This implementation does the fitting by maximizing the likelihood function, using the gradient information.
The R equivalent functions are garch in tseries and garchFit in fGarch.
| Modifier and Type | Class and Description |
|---|---|
static class |
GARCH.GRADIENT
the gradient information used to guild the optimization search
|
| Constructor and Description |
|---|
GARCH(TimeSeries xt,
int p,
int q)
Fit the GARCH(p, q) getModel to the time series.
|
GARCH(TimeSeries xt,
int p,
int q,
int maxIterations,
GARCH.GRADIENT grad)
Fit the GARCH(p, q) getModel to the time series.
|
| Modifier and Type | Method and Description |
|---|---|
GARCHModel |
getModel()
Get the fitted GARCH getModel.
|
public GARCH(TimeSeries xt, int p, int q, int maxIterations, GARCH.GRADIENT grad)
xt - a time series of the observationsq - the ARCH orderp - the GARCH part ordermaxIterations - the maximum number of iterations in the numerical optimization algorithmpublic GARCH(TimeSeries xt, int p, int q)
xt - a time series of the observationsq - the ARCH orderp - the GARCH part orderpublic GARCHModel getModel()