Nonlinear Dynamics and Statistics [Hardcover]

This book describes the state of the art in nonlinear dynamical reconstruction theory. The chapters are based upon a workshop held at the Isaac Newton Institute, Cambridge University, UK, in late 1998. The book's chapters present theory and methods topics by leading researchers in applied and theoretical nonlinear dynamics, statistics, probability, and systems theory.

Features and topics:

* disentangling uncertainty and error: the predictability of nonlinear systems

* achieving good nonlinear models

* delay reconstructions: dynamics vs. statistics

* introduction to Monte Carlo Methods for Bayesian Data Analysis

* latest results in extracting dynamical behavior via Markov Models

* data compression, dynamics and stationarity

Professionals, researchers, and advanced graduates in nonlinear dynamics, probability, optimization, and systems theory will find the book a useful resource and guide to current developments in the subject.

All models are lies. The Earth orbits the sun in an ellipse with the sun at one focus is false, but accurate enough for almost all purposes. This book describes the current state of the art of telling useful lies about time-varying systems in the real world. Specifically, it is about trying to understand (that is, tell useful lies about) dynamical systems directly from observa? tions, either because they are too complex to model in the conventional way or because they are simply ill-understood. B(:cause it overlaps with conventional time-series analysis, building mod? els of nonlinear dynamical systems directly from data has been seen by some observers as a somewhat ill-informed attempt to reinvent time-series analysis. The truth is distinctly less trivial. It is surely impossible, except in a few special cases, to re-create Newton's astonishing feat of writing a short equalı