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[Aerr, werr]=arconf(A, C, w, ... ARCONF Confidence intervals for AR coefficients.
[R, scale]=arqr(v, p, mcor) ARQR QR factorization for least squares estimation of AR model.
[]=acf(x, k, caption) ACF Plot of sample autocorrelation function.
[siglev,res]=arres(w,A,v,k) ARRES Test of residuals of fitted AR model.
[v]=arsim(w,A,C,n,ndisc) ARSIM Simulation of AR process.
[w, A, C, sbc, fpe, th]=arfit... ARFIT Stepwise least squares estimation of multivariate AR model.
armode(A, C, th) ARMODE Eigendecomposition of AR model.
arord(R, m, mcor, ne, pmin, p... ARORD Evaluates criteria for selecting the order of an AR model.
ox=adjph(x) ADJPH Normalization of columns of a complex matrix.
t=tquant(n, p) TQUANT Quantiles of Student's t distribution
ardem.m
ARfit: Fitting Multivariate A...
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5.0 | 7 ratings Rate this file 38 Downloads (last 30 days) File Size: 396.15 KB File ID: #174

ARfit

08 Feb 2000 (Updated 17 Jul 2006)

Estimation of parameters and eigenmodes of multivariate autoregressive models.

File Information

Description

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.

MATLAB release

MATLAB 6.0 (R12)

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Everyone's Tags	autoregressive, confidence intervals(2), estimation, multivariate, probability, statistics
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Comments and Ratings (7)
23 Jul 2003	Louis PAUL
02 Mar 2004	David Gowing
18 Jun 2005	Wei Wu
28 Mar 2006	ji xiaoyan
27 Apr 2006	Aslak Grinsted
06 Sep 2006	Alessandro Beda	Good software, however I think I found a bug in 'arres.m', that leads to output "NaN" as significance level. This is related to the fact that the first values of the computed residuals are NaNs. To correct the bug change line 53 wit h the following: res=res(p+1:end,:)-ones(n-p,1)*nanmean(res);
13 May 2009	C Schwalm

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Updates
30 Apr 2002	Update of software.
01 May 2002	Correction of description.
17 Jul 2006	Update for compatibility with Matlab 7.2