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ANALYSIS OF A MULTIVARIATE AUTOREGRESSIVE PROCESS

✍ Scribed by J. Lardies

Publisher
Elsevier Science
Year
1996
Tongue
English
Weight
273 KB
Volume
10
Category
Article
ISSN
0888-3270

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✦ Synopsis

This paper deals with the estimation of the order, the parameters, and the spectrum of a process modeled by a multivariate autoregressive time series. When large samples are available, the order of a noisy multivariate autoregressive process is determined (independently of the probability law governing the observed data), by minimisation of a new criterion function. Once the order is determined, the estimation of the autoregressive coefficients and the noise covariance matrices, which are strongly consistent, is derived. Asymptotic distribution functions of the parameter estimators are then obtained. To illustrate the procedure for identifying the order, the parameters and then estimating the spectrum of a noisy multivariate autoregressive process a numerical example is treated.

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