Algorithm 808: ARfit - A matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models
ARFIT is a collection of Matlab modules for modeling and analyzing multivariate time series with autoregressive (AR) models. ARFIT contains modules for fitting AR models to given time series data, for analyzing eigenmodes of a fitted model, and for simulating AR processes. ARFIT estimates the parameters of AR models from given time series data with a stepwise least squares algorithm that is computationally efficient, in particular when the data are high-dimensional. ARFIT modules construct approximate confidence intervals for the estimated parameters and compute statistics with which the adequacy of a fitted model can be assessed. Dynamical characteristics of the modeled time series can be examined by means of a decomposition of a fitted AR model into eigenmodes and associated oscillation periods, damping times, and excitations. The ARFIT module that performs the eigendecomposition of a fitted model also constructs approximate confidence intervals for the eigenmodes and their oscillation periods and damping times.
algorithms matlab eigenmodes least squares confidence intervals documentation model identification order selection parameter estimation principal oscillation pattern