Class AutoCovariance
- java.lang.Object
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- dev.nm.analysis.function.rn2r1.AbstractRealScalarFunction
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- dev.nm.analysis.function.rn2r1.AbstractBivariateRealFunction
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- dev.nm.stat.timeseries.linear.univariate.AutoCovarianceFunction
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- dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma.AutoCovariance
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- All Implemented Interfaces:
Function<Vector,Double>
,BivariateRealFunction
,RealScalarFunction
public class AutoCovariance extends AutoCovarianceFunction
Computes the Auto-CoVariance Function (ACVF) for an AutoRegressive Moving Average (ARMA) model by recursion. The R equivalent functions areARMAacf
andTacvfAR
in packageFitAR
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Nested Class Summary
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Nested classes/interfaces inherited from interface dev.nm.analysis.function.Function
Function.EvaluationException
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Constructor Summary
Constructors Constructor Description AutoCovariance(ARMAModel model)
Computes the auto-covariance function for an ARMA model.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
evaluate(double n)
Gets the i-th auto-covariance.double
evaluate(double i, double j)
Evaluate y = f(x1,x2).double
psi(int j)
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Methods inherited from class dev.nm.stat.timeseries.linear.univariate.AutoCovarianceFunction
get
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Methods inherited from class dev.nm.analysis.function.rn2r1.AbstractBivariateRealFunction
evaluate
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Methods inherited from class dev.nm.analysis.function.rn2r1.AbstractRealScalarFunction
dimensionOfDomain, dimensionOfRange
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Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Methods inherited from interface dev.nm.analysis.function.Function
dimensionOfDomain, dimensionOfRange
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Constructor Detail
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AutoCovariance
public AutoCovariance(ARMAModel model)
Computes the auto-covariance function for an ARMA model.- Parameters:
model
- an ARIMA model
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Method Detail
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evaluate
public double evaluate(double i, double j)
Description copied from interface:BivariateRealFunction
Evaluate y = f(x1,x2).- Parameters:
i
- x1j
- x2- Returns:
- f(x1, x2)
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evaluate
public double evaluate(double n)
Gets the i-th auto-covariance.- Parameters:
n
- the lag order- Returns:
- the i-th auto-covariance
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psi
public double psi(int j)
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