Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data
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$135.95$122.36 - Hardback: 631 pages
- Published: November 2010
- ISBN: 978-1-4398199-7-5
- Publisher: CRC Press
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- Edited by Stephen J. Guastello, and Robert A.M. Gregson.
A compilation of research methods and reflecting the expertise of the major contributors to NDS psychology, this book examines the techniques that have proven to be most useful in the behavioral sciences. This book is designed to develop skill and expertise in framing hypotheses dynamically and in building viable analytic models to test them. It addresses topics and methods of current interest in an application driven manner, making the book useful to the behavioral sciences community, as well as those in engineering, medicine, and other fields who are interested in nonlinear dynamics.
Table of Contents
Introduction to Nonlinear Dynamical Systems Analysis, R.A.M. Gregson and S.J. Guastello
Principles of Time Series Analysis, R.A.M. Gregson
Frequency Distributions and Error Functions, S.J. Guastello
Phase Space Analysis and Unfolding, M. Shelhamer
Nonlinear Dynamical Analysis of Noisy Time Series, A. Heathcote and D. Elliott
The Effects of the Irregular Sample and Missing Data in Time Series Analysis, D.M. Kreindler and C.J. Lumsden
A Dynamical Analysis via the Extended-Return-Map, J.-S. Li, J. Krauth, and J.P. Huston
Adjusting Behavioral Methods When Applying Nonlinear Dynamical Measures to Stimulus Rates, B.B. Frey
Entropy, S.J. Guastello
Analysis of Recurrence: Overview and Application to Eye-Movement Behavior, D.J. Aks
Discontinuities and Catastrophes with Polynomial Regression, S.J. Guastello
Nonlinear Regression and Structural Equations, S.J. Guastello
Catastrophe Models with Nonlinear Regression, S.J. Guastello
Catastrophe Model for the Prospect-Utility Theory Question, T.A. Oliva and S.R. McDade
Measuring the Scaling Properties of Temporal and Spatial Patterns: From the Human Eye to the Foraging Albatross, M.S. Fairbanks and R.P. Taylor
Oscillators with Differential Equations, J. Butner and T.N. Story
Markov Chains for Identifying Nonlinear Dynamics, S.J. Merrill
Markov Chain Example: Transitions between Two Pictorial Attractors, R.A.M. Gregson
Identifying Ill-Behaved Nonlinear Processes without Metrics: Use of Symbolic Dynamics, R.A.M. Gregson
Information Hidden in Signals and Macromolecules I: Symbolic Time-Series Analysis, M.A. Jiménez-Montaño, R. Feistel, and O. Diez-Martínez
Orbital Decomposition: Identification of Dynamical Patterns in Categorical Data, S.J. Guastello
Orbital Decomposition for Multiple Time-Series Comparisons, D. Pincus, D.L. Ortega, and A.M. Metten
The Danger of Wishing for Chaos, P.E. McSharry
Methodological Issues in the Application of Monofractal Analyses in Psychological and Behavioral Research, D. Delignières, K. Torre, and L. Lemoine
Frontiers of Nonlinear Methods, R.A.M. Gregson
Index
Author/Editor Biography
Stephen Gaustello is a professor of Psychology at Marquette University, in Milwaukee Wisconsin.
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