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Nonlinear Dynamics and Time Series

Nonlinear Dynamics and Time Series

Building a Bridge Between the Natural and Statistical Sciences

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  • Release Date: 30/08/2006
  • Barcode: 9780821841853
  • Imprint: American Mathematical Society
  • Publisher: American Mathematical Society
Nonlinear Dynamics and Time Series

Nonlinear Dynamics and Time Series

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DESCRIPTION

Building a Bridge Between the Natural and Statistical Sciences
A collection of research and expository papers reflecting the interfacing of two fields: nonlinear dynamics and statistics. It presents the proceedings of a workshop entitled 'Nonlinear Dynamics and Time Series: Building a Bridge Between the Natural and Statistical Sciences' held at the Centre de Recherches Mathematiques in Montreal in July 1995.
This book is a collection of research and expository papers reflecting the interfacing of two fields: nonlinear dynamics (in the physiological and biological sciences) and statistics. It presents the proceedings of a four-day workshop entitled ""Nonlinear Dynamics and Time Series: Building a Bridge Between the Natural and Statistical Sciences"" held at the Centre de Recherches Mathematiques (CRM) in Montreal in July 1995. The goal of the workshop was to provide an exchange forum and to create a link between two diverse groups with a common interest in the analysis of nonlinear time series data. The editors and peer reviewers of this work have attempted to minimize the problems of maintaining communication between the different scientific fields. The result is a collection of interrelated papers that highlight current areas of research in statistics that might have particular applicability to nonlinear dynamics and new methodology and open data analysis problems in nonlinear dynamics that might find their way into the toolkits and research interests of statisticians.Features: A survey of state-of-the-art developments in nonlinear dynamics time series analysis with open statistical problems and areas for further research. Contributions by statisticians to understanding and improving modern techniques commonly associated with nonlinear time series analysis, such as surrogate data methods and estimation of local Lyapunov exponents. Starting point for both scientists and statisticians who want to explore the field. Expositions that are readable to scientists outside the featured fields of specialization. Information for our distributors: Titles in this series are co-published with the Fields Institute for Research in Mathematical Sciences (Toronto, Ontario, Canada).

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