mAr.eig: Eigendecomposition of m-variate AR(p) model

In mAr: Multivariate AutoRegressive Analysis

Eigendecomposition of m-variate AR(p) model

Description

Eigen-decomposition of the estimated matrix of autoregressive coefficients from an m-variate AR(p) model

Usage

mAr.eig(A, C = NULL, ...)

Arguments

A	matrix of estimated autoregression coefficients
C	noise covariance matrix
...	additional arguments for specific methods

Value

A list with components:

modes	periods and damping times associated to each eigenmode
eigv	m*p m-dimensional eigenvectors

Author(s)

S. M. Barbosa

References

Barbosa S.M., Silva M.E., Fernandes M.J. (2006), Multivariate autoregressive modelling of sea level time series from TOPEX/Poseidon satellite altimetry. Nonlinear Processes in Geophysics, 13, 177-184.

Neumaier, A. and Schneider, T. (2001), Estimation of parameters and eigenmodes of multivariate autoregressive models. ACM Transactions on Mathematical Software, 27, 1, 27-57.

Schneider, T. and Neumaier, A. (2001), A Matlab package fo the estimation of parameters and eigenmodes of multivariate autoregressive models, 27, 1, 58-65.

Examples

data(pinkham)
y=mAr.est(pinkham,2,5)
mAr.eig(y$AHat,y$CHat)

mAr documentation built on June 1, 2022, 1:07 a.m.