
Accession Number : ADA186548
Title : The Linear Dependency Structure of Covariance Nonstationary Time Series.
Descriptive Note : Technical rept.,
Corporate Author : NAVAL POSTGRADUATE SCHOOL MONTEREY CA
Personal Author(s) : Gersch, Will
PDF Url : ADA186548
Report Date : Jun 1987
Pagination or Media Count : 38
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. Keywords: Information theory; Time series; Time varying model; Autoregression; Feedback; Casuality; Electroencephalogram.
Descriptors : *INFORMATION THEORY, *MODELS, *STRUCTURAL PROPERTIES, *TIME SERIES ANALYSIS, *COVARIANCE, DENSITY, ELECTROENCEPHALOGRAPHY, FEEDBACK, LINEARITY, MULTIVARIATE ANALYSIS, PARAMETRIC ANALYSIS, POWER SPECTRA, TIME, MATHEMATICAL MODELS, EPILEPSY, VECTOR ANALYSIS, REGRESSION ANALYSIS
Subject Categories : Cybernetics
Statistics and Probability
Numerical Mathematics
Medicine and Medical Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE