Some Theory of Statistical Inference for Nonlinear Science
AbstractThis article shows how standard errors can be estimated for a measure of the number of excited degrees of freedom (the correlation dimension), a measure of the rate of information creation (a proxy for the Kolmogorov entropy), and a measure of instability. These measures are motivated by nonlinear science and chaos theory. The main analytical method is central limit theory of U-statistics for mixing processes. The paper takes a step toward formal hypothesis testing in nonlinear science and chaos theory. Copyright 1991 by The Review of Economic Studies Limited.
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Bibliographic InfoArticle provided by Wiley Blackwell in its journal Review of Economic Studies.
Volume (Year): 58 (1991)
Issue (Month): 4 (July)
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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0034-6527
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