Reparametrization of autoregressive models with coefficients depending on covariables: application to EEG spectrum maturation.
To describe the spectral characteristics of the EGG development through autoregressive (AR) time series models it is necessary to perform regression analysis of the AR parameters with regards to the age of the subject. A major difficulty in this approach is the very complex nature of the admissible region of the AR coefficients, which impedes the straight use of regression techniques. The present paper overcomes this difficulty by first applying the Barndoff-Nielsen and Schou reparametrization of AR models, followed by Fisher's transformation and then carrying out age regression analysis of the transformed parameters. We apply this approach to real EEG data obtained from a normative sample of subjects in the age range from 5 to 95 years.
Clark
I
I
Cuban Neuroscience Center, Havana, Cuba.
Biscay
R
R
Jiménez
J C
JC
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D002648:Child; D002675:Child, Preschool; D004569:Electroencephalography; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D012016:Reference Values; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted