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Beschreibung
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 allow to 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, but its widest use is likely to be by practitioners who seek new tools to address social scientific questions in new ways.
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 allow to 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, but its widest use is likely to be by practitioners who seek new tools to address social scientific questions in new ways.
Über den Autor

Sebastian Wallot obtained his diploma in psychology from the University of Trier (Germany) and his PhD in experimental psychology from the University of Cincinnati, OH (USA). After postdoctoral positions at the University of Aarhus (Denmark) and the Max Planck Institute for Empirical Aesthetics in Frankfurt at the Main (Germany), he is currently working as Professor for research methods in psychology at Leuphana University of Lüneburg (Germany). His research if focused on joint action and reading from a dynamic systems perspective. Moreover, he is developing new analysis tools for time series - particularly in the area of recurrence and fractal analysis.

Inhaltsverzeichnis
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
Details
Erscheinungsjahr: 2025
Genre: Importe, Soziologie
Rubrik: Wissenschaften
Medium: Taschenbuch
Reihe: Quantitative Applications in the Social Sciences
ISBN-13: 9781071872338
ISBN-10: 1071872338
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Wallot, Sebastian
Leonardi, Giuseppe
Auflage: 1. Auflage
Hersteller: SAGE Publications, Inc
Quantitative Applications in the Social Sciences
Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 216 x 140 x 9 mm
Von/Mit: Sebastian Wallot (u. a.)
Erscheinungsdatum: 24.01.2025
Gewicht: 0,201 kg
Artikel-ID: 130505147

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