Giuseppe Leonardi, Sebastian Wallot

Recurrence-Based Analyses

• Broschiertes Buch

Produktbeschreibung

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. 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.

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Produktdetails

• Verlag: SAGE Publications Inc
• Seitenzahl: 152
• Erscheinungstermin: 14. April 2025
• Englisch
• Abmessung: 215mm x 139mm
• ISBN-13: 9781071872338
• ISBN-10: 1071872338
• Artikelnr.: 72175442

Inhaltsangabe

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