Class ARMAForecastMultiStep
- java.lang.Object
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- dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma.ARMAForecastMultiStep
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public class ARMAForecastMultiStep extends Object
Computes the h-step ahead prediction of a causal ARMA model, by the innovative algorithm.
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Constructor Summary
Constructors Constructor Description ARMAForecastMultiStep(double[] xt, ARMAModel arma, int h)
Makes the h-step ahead prediction for an ARMA model.ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma)
Makes the one-step ahead prediction for an ARMA model.ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h)
Makes the h-step ahead prediction for an ARMA model.ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h, InnovationsAlgorithm inn)
Makes the h-step ahead prediction for an ARMA model.ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h, InnovationsAlgorithm inn, ARMAForecastOneStep forecast1)
Makes the h-step ahead prediction for an ARMA model.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Vector
allForecasts()
Gets all the predictions of the next h steps in one vector.Vector
allMSEs()
Gets all the mean squared errors (MSE) of the h-step ahead predictions.ARMAForecastOneStep
getARMAForecastOneStep()
Gets the auxiliary ARMA one-step ahead forecaster.InnovationsAlgorithm
getStandardError()
Gets the the auxiliary coefficients, Θ and V, in using the innovative algorithm.double
var()
Gets the mean squared error of the h-step ahead prediction.double
xHat()
Gets the h-step ahead prediction of the time series.
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Constructor Detail
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ARMAForecastMultiStep
public ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h, InnovationsAlgorithm inn, ARMAForecastOneStep forecast1)
Makes the h-step ahead prediction for an ARMA model.- Parameters:
xt
- the observationsarma
- the ARMA modelh
- a time stepinn
- the innovation algorithm to useforecast1
- the auxiliary one-step ahead forecast ofxt
usingarma
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ARMAForecastMultiStep
public ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h, InnovationsAlgorithm inn)
Makes the h-step ahead prediction for an ARMA model.- Parameters:
xt
- the observationsarma
- the ARMA modelh
- a time stepinn
- the innovations
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ARMAForecastMultiStep
public ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma, int h)
Makes the h-step ahead prediction for an ARMA model.- Parameters:
xt
- the observationsarma
- the ARMA modelh
- a time step
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ARMAForecastMultiStep
public ARMAForecastMultiStep(double[] xt, ARMAModel arma, int h)
Makes the h-step ahead prediction for an ARMA model.- Parameters:
xt
- the observationsarma
- the ARMA modelh
- a time step
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ARMAForecastMultiStep
public ARMAForecastMultiStep(IntTimeTimeSeries xt, ARMAModel arma)
Makes the one-step ahead prediction for an ARMA model.- Parameters:
xt
- the observationsarma
- the ARMA model
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Method Detail
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xHat
public double xHat()
Gets the h-step ahead prediction of the time series.- Returns:
- the h-step ahead prediction
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allForecasts
public Vector allForecasts()
Gets all the predictions of the next h steps in one vector.- Returns:
- all the predictions of the next h steps
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var
public double var()
Gets the mean squared error of the h-step ahead prediction.- Returns:
- the mean squared error (variance)
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allMSEs
public Vector allMSEs()
Gets all the mean squared errors (MSE) of the h-step ahead predictions.- Returns:
- the mean squared errors (variance) of all h steps
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getStandardError
public InnovationsAlgorithm getStandardError()
Gets the the auxiliary coefficients, Θ and V, in using the innovative algorithm.- Returns:
- the the auxiliary coefficients, Θ and V, in using the innovative algorithm
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getARMAForecastOneStep
public ARMAForecastOneStep getARMAForecastOneStep()
Gets the auxiliary ARMA one-step ahead forecaster.- Returns:
- the auxiliary ARMA one-step ahead forecaster
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