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Recurrence-Based Analyses
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Recurrence-Based Analyses



February 2025 | 136 pages | SAGE Publications, Inc
This book introduces techniques developed in physics and physiology for characterizing and analyzing patterns in time series data to a broad audience of social scientists. In contrast to time-series regression and related techniques, recurrence quantification analysis (RQA) has its background in chaos and nonlinear dynamical systems—theory arguably very relevant to social processes. The goal of Recurrence-Based Analyses is to introduce readers to these techniques that can characterize a system’s complexity, stability and instability, and conditions under which it transitions from one state to another. The authors illustrate concepts and techniques with relevant social science examples at different temporal scales: biweekly polling data on federal elections in Germany; daily values of three stock market indices; daily cases of SarsCov-19 in four countries during the pandemic; and second-by-second vocalizations of mothers and infants interacting recorded by motion cameras. This introduction to RQA serves as a useful supplement to undergraduate and graduate courses in computational social science, and also by researchers who seek new tools to address social scientific questions in new ways.
 
Series Editor Introduction
 
Acknowledgments
 
About the Authors
 
Acronyms and Notation
 
Chapter 1: What is Recurrence Analysis?
The Recurrence Plot

 
Deriving Recurrence Measures

 
Advantages and Limitations of Recurrence Analysis

 
 
Chapter 2: The Basics of Recurrence Analysis—Univariate RQA
Parameter Estimation

 
The Delay Parameter t

 
The Embedding Parameter m

 
The Radius Parameter e

 
Further Parameters

 
Summarizing RQA Outputs

 
 
Chapter 3: The Bi-Variate Case: Cross-Recurrence Quantification Analysis
Introduction to CRQA

 
Standardization

 
Alignment

 
The Cross-Recurrence Plot (CRP)

 
Using CRQA With Continuous Data: Stock Market Fluctuations

 
Using CRQA With Categorical Data

 
 
Chapter 4: The Diagonal-Wise Cross-Recurrence Profile (DCRP)
Diagonal-Wise Cross Recurrence Profiles (DCRP)

 
Building a Baseline by Means of Shuffling

 
 
Chapter 5: Windowed Recurrence Analysis
Introduction to Univariate Windowed Recurrence Analysis

 
Windowed Cross-Recurrence Analysis

 
Using Windowed Recurrence Analysis for Continuous Monitoring

 
 
Chapter 6: Multivariate Analysis: Multidimensional Recurrence Quantification Analysis (MdRQA)
Introduction to MdRQA

 
Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)

 
An Example Using Multidimensional RQA on Political Polling Data

 
 
Chapter 7: Sample Analysis and Practicalities
Calculating General Parameters

 
Time Series Length

 
Computing Confidence Bounds Via Boot-Strapping

 
Parameter Exploration

 
Surrogate Analysis

 
Dealing With Multiple Recurrence-Measures

 
 
Chapter 8: Conclusion
Further Applications

 
Finding Software

 
A Final Note

 
 
References
 
Index

This book is a solid introduction to recurrence-based analysis. It is very accessible. The authors explain the basic elements in clear
language that most methodologically-oriented students will find understandable. The book is also surprisingly comprehensive for such an
introductory treatment.

Courtney Brown
Emory University

The authors provide a clear and concise introduction that makes an advanced topic accessible to a broad audience.

Clayton Webb
University of Kansas

This book provides an intuitive introduction to a topic with much potential for social science applications, but one whose daunting mathematical demands have made it inaccessible to most students and scholars.

David McDowall
University at Albany-SUNY

This book presents an advanced quantitative technique to social science researchers in a clear and precise manner, offering a perfect balance of technical depth and accessibility.

Duan Zhang
University of Denver

For instructors

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Paperback
ISBN: 9781071872338
£36.99