ARfit: A Matlab package for the estimation of parameters and
eigenmodes of multivariate autoregressive models
ARfit is a collection of
Matlab modules for
- estimating parameters of multivariate autoregressive (AR)
models,
- diagnostic checking of fitted AR models, and
- analyzing eigenmodes of fitted AR models.
The algorithms implemented in ARfit are described in the following
papers, which should be referenced if you use ARfit in
publications:
A. Neumaier and T. Schneider, 2001: Estimation
of parameters and eigenmodes of multivariate autoregressive
models. ACM Trans. Math. Softw., 27,
2757.
T. Schneider and A. Neumaier, 2001: Algorithm
808: ARfit - A Matlab package for the estimation of parameters and
eigenmodes of multivariate autoregressive models. ACM
Trans. Math. Softw., 27, 5865.
ARfit has been successfully tested under Matlab 3 and later
versions, up to Matlab 7.2.
Last ARfit revision: 14 July 2006
The ARfit package consists of a number of Matlab modules, the
file CHANGES with a history of recent
revisions of the programs, and the above papers.
To install ARfit, copy the package (available as a zip-archive) into a directory that is accessible by
Matlab. Unpack the package using
unzip arfit.zip
on Unix/Linux platforms or an equivalent command on other
platforms.
Starting Matlab and invoking Matlab's online help function
help filename
calls up detailed information on the purpose and the calling
syntax of the module filename.m . The script
ardem.m demonstrates the basic features of the modules contained
in ARfit.
If you experience problems downloading ARfit in the packaged
form, you may want to download the ARfit files individually.
- CHANGES
- A history of recent changes to ARfit.
- acf.m
- Plots the sample autocorrelation function of a univariate time
series (using XCORR from the Matlab Signal Processing Toolbox).
- adjph.m (auxiliary
routine)
- Multiplies a complex vector by a phase factor such that the
real part and the imaginary part of the vector are orthogonal
and the norm of the real part is greater than or equal to the
norm of the imaginary part. ADJPH is required by ARMODE to
normalize the eigenmodes of an AR model.
- arconf.m
- Computes approximate confidence intervals for the AR model
coefficients.
- ardem.m
- Demonstrates the use of modules contained in the ARfit package.
- arfit.m
- Stepwise selection of the order of an AR model and least
squares estimation of AR model parameters.
- arfit.pdf
- Published description of the algorithms.
- arfit_alg.pdf
- Published note on using ARfit.
- armode.m
- Eigendecomposition of AR model. For a fitted AR model,
ARMODE computes eigenmodes and their associated oscillation
periods and damping times, as well as approximate confidence
intervals for the eigenmodes, periods, and damping times.
- arord.m (auxiliary
routine)
- Computes approximate order selection criteria for a sequence
of AR models. ARORD is required by ARFIT.
- arqr.m (auxiliary
routine)
- QR factorization for least squares estimation of AR
model parameters. ARQR is required by ARFIT.
- arres.m
- Diagnostic checking of the residuals of a fitted
model. Computes the time series of residuals. The modified
multivariate portmanteau statistic of Li & McLeod (1981) is
used to test the residuals for uncorrelatedness.
- arsim.m
- Simulation of AR processes.
- tquant.m (auxiliary
routine)
- Quantiles of Student's t distribution. (TQUANT is required by
ARCONF and ARMODE in the construction of confidence intervals.)
© Copyright
2001 by the Association for Computing
Machinery, Inc. This copy is posted by permission of ACM and
may not be redistributed.
Tapio
Schneider
California Institute of Technology
Mail Code 100-23
1200 E. California Blvd.
Pasadena, CA 91125
|
Arnold
Neumaier
Institut für Mathematik
Universität Wien
A-1090 Wien
Austria
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