com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arma
Interface ARMAFitting

All Known Implementing Classes:

ConditionalSumOfSquares

public interface ARMAFitting

This interface represents a fitting method for estimating φ, θ, μ, σ² in an ARMA model.

See Also:

ConditionalSumOfSquares

Method Summary

double	AIC() Compute the AIC of fitted model.
double	AICC() Compute the AICC of fitted model.
Matrix	covariance() Get the asymptotic covariance matrix of the estimators.
ARIMAModel	getModel() Get the fitted ARMA model.
Vector	stderr() Get the asymptotic standard errors of the estimators.
double	var() Get the variance of the white noise.

Method Detail

getModel

ARIMAModel getModel()

Get the fitted ARMA model.

Returns:

the fitted ARMA model

var

double var()

Get the variance of the white noise.

Returns:

σ²

stderr

Vector stderr()

Get the asymptotic standard errors of the estimators.

Returns:

the asymptotic standard errors of the estimators

covariance

Matrix covariance()

Get the asymptotic covariance matrix of the estimators.

Returns:

the asymptotic covariance matrix of the estimators

AIC

double AIC()

Compute the AIC of fitted model.

Returns:

the AIC

AICC

double AICC()

Compute the AICC of fitted model.

Returns:

the AICC