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Some Graphical Considerations in Time Series Analysis
May 1982 (vol. 4 no. 5)
pp. 493-499
ASCII Text
x 
 
Benjamin Kedem, "Some Graphical Considerations in Time Series Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 5, pp. 493-499, May, 1982.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.1982.4767293,
author = {Benjamin Kedem},
title = {Some Graphical Considerations in Time Series Analysis},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {4},
number = {5},
issn = {0162-8828},
year = {1982},
pages = {493-499},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.1982.4767293},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - Some Graphical Considerations in Time Series Analysis
IS - 5
SN - 0162-8828
SP493
EP499
EPD - 493-499
A1 - Benjamin Kedem,
PY - 1982
VL - 4
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
Benjamin Kedem, Department of Mathematics, University of Maryland, College Park, MD 20742.
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.
Citation:
Benjamin Kedem, "Some Graphical Considerations in Time Series Analysis," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 5, pp. 493-499, May 1982, doi:10.1109/TPAMI.1982.4767293
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