AMS eBook CollectionsOne of the world's most respected mathematical collections, available in digital format for your library or institution
Nonlinear Dynamics and Time Series: Building a Bridge Between the Natural and Statistical Sciences
About this Title
Colleen D. Cutler, University of Waterloo, Waterloo, ON, Canada and Daniel Theodore Kaplan, McGill University, Montreal, QC, Canada, Editors
Publication: Fields Institute Communications
Publication Year:
1997; Volume 11
ISBNs: 978-0-8218-4185-3 (print); 978-1-4704-2979-9 (online)
DOI: https://doi.org/10.1090/fic/011
MathSciNet review: MR1426609
MSC: Primary 62-06; Secondary 58F13, 58F40
ReadershipTable of Contents
Download chapters as PDF
Front/Back Matter
Chapters
- Henry Abarbanel – Tools for the analysis of chaotic data
- Howell Tong – Some comments on nonlinear time series analysis
- Colleen Cutler – A general approach to predictive and fractal scaling dimensions in discrete-index time series
- Louis Pecora, Thomas Carroll and James Heagy – Statistics for continuity and differentiability: An application to attractor reconstruction from time series
- Timothy Sauer – Reconstruction of integrate-and-fire dynamics
- Kung-sik Chan – On the validity of the method of surrogate data
- James Theiler and Dean Prichard – Using "Surrogate Surrogate Data" to calibrate the actual rate of false positives in tests for nonlinearity in time series
- Barbara Bailey, Stephen Ellner and Douglas Nychka – Chaos with confidence: Asymptotics and applications of local Lyapunov exponents
- Zhan-Qian Lu and Richard Smith – Estimating local Lyapunov exponents
- Peter Hall – Defining and measuring long-range dependence
- Peter Robinson and Paolo Zaffaroni – Modelling nonlinearity and long memory in time series
- Mark Berliner, Steven MacEachern and Catherine Forbes – Ergodic distributions of random dynamical systems
- Lisa Borland – Detecting structure in noise
- Martin Casdagli – Characterizing nonlinearity in weather and epilepsy data: A personal view
- Andre Longtin and Daniel Racicot – Assessment of linear and nonlinear correlations between neural firing events
- Stephen Merrill and John Cochran – Markov chain methods in the analysis of heart ratevariability