Review of Economic Studies Vol. 58 No. 4 1991

Some Theory of Statistical Inference for Nonlinear Science

William A. Brock¹; Ehung G. Baek²

¹ University of Wisconsin–Madison · ² Iowa State University

Abstract

This article shows how standard errors can be estimated for a measure of the number of excited degrees of freedom (the correlation dimension), and 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.

DOI

10.2307/2297828

Volume

58

Issue

4

Pages

697

Sources

crossref bibtex:phds-export.bib openalex

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