Table of Contents:
  • 1. Working with deterministic mathematical models
  • The argument in favor of the deterministic approach
  • Part I: 2. What is chaos?
  • Necessary conditions for chaos
  • Characteristics of chaos
  • 3. Measuring chaos
  • Lyapunov characteristic exponents
  • Fourier analysis
  • Phase space reconstruction of an attractor using data
  • The spatial correlation test
  • 4. Estimating chaos models
  • The problem of step size
  • Comparing the model's predicted values to the data
  • The future of chaotic studies in the social sciences
  • An alternative approach for maps
  • Part II: 5. What is a catastrophe?
  • Placing the cusp in the range of the data
  • 6. Strategies for specifying catastrophe models
  • 7. Estimating catastrophe models.