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Forecast entropy

Forecast entropy A technique, called forecast entropy, is proposed to measure the difficulty of forecasting data from an observed time series. When the series is chaotic, this technique can also determine the delay and embedding dimension used in reconstructing an attractor. An ideal random system is defined. An observed time series from the Lorenz system is used to show the results. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Forecast entropy

W. Yao; C. Essex; P. Yu; M. Davison
Kybernetes , Volume 33 (5/6): 7 – Jun 1, 2004
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References (14)

Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
0368-492X
DOI
10.1108/03684920410534056
Publisher site
See Article on Publisher Site

Abstract

A technique, called forecast entropy, is proposed to measure the difficulty of forecasting data from an observed time series. When the series is chaotic, this technique can also determine the delay and embedding dimension used in reconstructing an attractor. An ideal random system is defined. An observed time series from the Lorenz system is used to show the results.

Journal

Kybernetes – Emerald Publishing

Published: Jun 1, 2004

Keywords: Cybernetics; Statistical forecasting; Data analysis

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