Title :
Some Graphical Considerations in Time Series Analysis
Author_Institution :
Department of Mathematics, University of Maryland, College Park, MD 20742.
Abstract :
The pictorial information in a stationary time series as depicted by crossings of levels and crossings of random levels and related quantities is studied. It is shown that such graphical features are directly connected with the covariance function and hence with the spectral density. Many of these features can be actually applied in estimation and in the study of extremes. In the Gaussian case, the finite dimensional distributions are completely determined by the axis crossings and by the crossings of a random curve (to be defined) if the process is essentially bounded. Certain graphical patterns are suggested for a fast recognition of low-order ARMA models.
Keywords :
Gaussian processes; Graphics; Information analysis; Pattern recognition; Random variables; Spectral analysis; Time series analysis; Zinc; Clipping; crossings; features in time series; higher order crossings; pictorial information; random clipping; sojoums;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1982.4767293