Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data

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.

Stephen Gaustello is a professor of Psychology at Marquette University, in Milwaukee Wisconsin.

Introduction to Nonlinear Dynamical Systems Analysis, R.A.M. Gregson and S.J. GuastelloPrinciples of Time Series Analysis, R.A.M. GregsonFrequency Distributions and Error Functions, S.J. GuastelloPhase Space Analysis and Unfolding, M. ShelhamerNonlinear Dynamical Analysis of Noisy Time Series, A. Heathcote and D. ElliottThe Effects of the Irregular Sample and Missing Data in Time Series Analysis, D.M. Kreindler and C.J. LumsdenA Dynamical Analysis via the Extended-Return-Map, J.-S. Li, J. Krauth, and J.P. HustonAdjusting Behavioral Methods When Applying Nonlinear Dynamical Measures to Stimulus Rates, B.B. FreyEntropy, S.J. GuastelloAnalysis of Recurrence: Overview and Application to Eye-Movement Behavior, D.J. AksDiscontinuities and Catastrophes with Polynomial Regression, S.J. GuastelloNonlinear Regression and Structural Equations, S.J. GuastelloCatastrophe Models with Nonlinear Regression, S.J. GuastelloCatastrophe Model for the Prospect-Utility Theory Question, T.A. Oliva and S.R. McDadeMeasuring the Scaling Properties of Temporal and Spatial Patterns: From the Human Eye to the Foraging Albatross, M.S. Fairbanks and R.P. TaylorOscillators with Differential Equations, J. Butner and T.N. StoryMarkov Chains for Identifying Nonlinear Dynamics, S.J. MerrillMarkov Chain Example: Transitions between Two Pictorial Attractors, R.A.M. GregsonIdentifying Ill-Behaved Nonlinear Processes without Metrics: Use of Symbolic Dynamics, R.A.M. GregsonInformation Hidden in Signals and Macromolecules I: Symbolic Time-Series Analysis, M.A. Jiménez-Montaño, R. Feistel, and O. Diez-MartínezOrbital Decomposition: Identification of Dynamical Patterns in Categorical Data, S.J. GuastelloOrbital Decomposition for Multiple Time-Series Comparisons, D. Pincus, D.L. Ortega, and A.M. MettenThe Danger of Wishing for Chaos, P.E. McSharryMethodological Issues in the Application of Monofractal Analyses in Psychological and Behavioral Research, D. Delignières, K. Torre, and L. LemoineFrontiers of Nonlinear Methods, R.A.M. GregsonIndex