Class AR1GARCH11Model
- java.lang.Object
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- dev.nm.stat.timeseries.linear.univariate.stationaryprocess.armagarch.ARMAGARCHModel
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- dev.nm.stat.timeseries.linear.univariate.stationaryprocess.armagarch.AR1GARCH11Model
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public class AR1GARCH11Model extends ARMAGARCHModel
An AR1-GARCH11 model takes this form. \[ X_t = \mu + \phi X_{t-1} + \epsilon_t \\ h_t = \alpha_0 + \alpha_1 e_{t-1}^2 + \beta_1 h_{t-1} \]
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Constructor Summary
Constructors Constructor Description AR1GARCH11Model(double mu, double phi, double a0, double a1, double b1)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
a0()
Gets the constant coefficient.double
alpha()
Gets the ARCH coefficient.double
beta()
Gets the GARCH coefficient.double
conditionalMean(double x)
Compute the univariate AR1 conditional mean, given the last lag.double
sigma2(double e2, double sigma2_lag)
Computes the conditional variance based on the past information.-
Methods inherited from class dev.nm.stat.timeseries.linear.univariate.stationaryprocess.armagarch.ARMAGARCHModel
getARMAModel, getGARCHModel
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Method Detail
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a0
public double a0()
Gets the constant coefficient.- Returns:
- the constant coefficient
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alpha
public double alpha()
Gets the ARCH coefficient.- Returns:
- the ARCH coefficient
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beta
public double beta()
Gets the GARCH coefficient.- Returns:
- the GARCH coefficient
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sigma2
public double sigma2(double e2, double sigma2_lag)
Computes the conditional variance based on the past information.- Parameters:
e2
- the last squared observationsigma2_lag
- the last conditional variance- Returns:
- the conditional variance, h(t | Ft)
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conditionalMean
public double conditionalMean(double x)
Compute the univariate AR1 conditional mean, given the last lag.- Parameters:
x
- the last AR lags- Returns:
- the conditional mean
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