Introduction to Nonlinear Dynamical Systems and Analysis
An INSTATS supported seminar/workshop
Understanding the complexities of social, health, and physical systems presents a formidable challenge for researchers across the sciences. Traditional linear models often fail to capture real-world phenomena' dynamic and nonlinear nature. Enter nonlinear dynamical systems, a robust framework that allows researchers to explore how entities interact and evolve over time, leading to emergent behavior and complex data patterns that go beyond what traditional forms of data analysis can accommodate. Participants will engage with classic nonlinear dynamics concepts such as fixed points and their stability and state space, concepts that offer profound insights into phenomena across the social, behavioral, health, and physical sciences - and learn to use these concepts in empirical settings. The integration of R as the primary software for analysis provides a practical and versatile platform for modeling and analysis of nonlinear systems, ensuring attendees leave with actionable skills applicable to their research and a collection of R scripts to help them use their new skills.
Outline
The seminar will be delivered via Zoom on January 13th and 14th, 2025, from 1600 UTC to 2100 UTC each day.
Day 1:
• Session 1: What are nonlinear dynamical systems?
• Session 2: State spaces and fixed points
Day 2
• Session 3: Attractors, stability, manifolds
• Session 4: Systems dynamics and formal models
Who should attend: This seminar is suitable for anyone with basic knowledge of linear regression and R who wishes to learn about nonlinear approaches to data analysis and theorizing. It was explicitly designed for social- and behavioral-science PhD students and researchers interested in pushing the boundaries of their disciplines, but it also is appropriate and valuable for any discipline that uses time-series data, including economic, ecological, and biomedical fields.
For more information and to register, please go to: https://instats.org/seminar/introduction-to-nonlinear-dynamical-syst2.
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Barney Ricca
Lyda Hill Institute for Human Resilience
University of Colorado Colorado Springs
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