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Statistical Inference Theory Using Finite and Noisy Data Sets

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Abstract

The statistical properties of the correlation integral and the correlation dimension are discussed in the context of finite and noise infected data sets. Stochastic processes are defined and discussed in the context of hypothesis testing and time series modeling. Applications of the presented statistical techniques are discussed within the general goal of increased accuracy of linear and nonlinear time series model specification.

© 1991 Optical Society of America

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