Package dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma

Class AutoCovariance

java.lang.Object

dev.nm.analysis.function.rn2r1.AbstractRealScalarFunction

dev.nm.analysis.function.rn2r1.AbstractBivariateRealFunction

dev.nm.stat.timeseries.linear.univariate.AutoCovarianceFunction

dev.nm.stat.timeseries.linear.univariate.stationaryprocess.arma.AutoCovariance

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 are ARMAacf and TacvfAR in package FitAR.

Nested Class Summary

Nested classes/interfaces inherited from interface dev.nm.analysis.function.Function

Function.EvaluationException

Constructor Summary

Constructors

Constructor	Description
AutoCovariance(ARMAModel model)	Computes the auto-covariance function for an ARMA model.

Method Summary

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)

Methods inherited from class dev.nm.stat.timeseries.linear.univariate.AutoCovarianceFunction

get

Methods inherited from class dev.nm.analysis.function.rn2r1.AbstractBivariateRealFunction

evaluate

Methods inherited from class dev.nm.analysis.function.rn2r1.AbstractRealScalarFunction

dimensionOfDomain, dimensionOfRange

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface dev.nm.analysis.function.Function

dimensionOfDomain, dimensionOfRange

Constructor Details

AutoCovariance

public AutoCovariance(ARMAModel model)

Computes the auto-covariance function for an ARMA model.

Parameters:

model - an ARIMA model

Method Details

evaluate

public double evaluate(double i,
 double j)

Description copied from interface: BivariateRealFunction

Evaluate y = f(x₁,x₂).

Parameters:

i - x₁

j - x₂

Returns:

f(x₁, x₂)

evaluate

public double evaluate(double n)

Gets the i-th auto-covariance.

Parameters:

n - the lag order

Returns:

the i-th auto-covariance

psi

public double psi(int j)