The Linear Dependency Structure of Covariance Nonstationary Time Series
Loading...
Authors
Gersch, Will
Subjects
Information theory
Time series
Time varying model
Autoregression
Feedback
Casuality
Electroencephalogram
Time series
Time varying model
Autoregression
Feedback
Casuality
Electroencephalogram
Advisors
Date of Issue
1987-06
Date
June 1987
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
The linear dependence, feedback and casuality structure of covariance nonstationary time series is developed. at every instant in time, the amount of linear dependence between time series vectors is expressible as the sum of the amount of feedback from the first time series vector to the second, the amount of feedback from the second time series to the first and the amount of instantaneous feedback. The parametric modeling of multivariate covariance nonstationary time series and the computation of their interdependency structure from the fitted model are also treated. The time series is modeled by a multivariate time varying autoregressive (MVTVAR) model. The fitted MVTVAR model yields an instantaneous power spectral density (IPSD) matrix, The IPSD is used in computing the linear dependency structure of nonstationary time series. An example of the modeling and the determination of instantaneous casuality from a human implanted electrode seizure event EEG is shown.
Type
Technical Report
Description
Prepared for: Naval Postgraduate School
Monterey, CA 93943-5000
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
NPS55-87-006
Sponsors
Funder
Format
40 p.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.