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rqa [2021/10/19 22:08] – utworzono zubekjrqa [2022/05/11 14:24] (aktualna) – Added demos zubekj
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 Recurrence (Quantification) Analysis (RQA) is a nonlinear data analysis technique used for studying dynamical systems. It can be applied to any time series coming from a dynamical system that repeats itself (conservative system) – most of the real-world complex phenomena fall into this category. Recurrence plot is a visual representation of a dynamical process. RQA measures quantify meaningful properties of the system (kind of organization, predictability, stability, etc.). Recurrence (Quantification) Analysis (RQA) is a nonlinear data analysis technique used for studying dynamical systems. It can be applied to any time series coming from a dynamical system that repeats itself (conservative system) – most of the real-world complex phenomena fall into this category. Recurrence plot is a visual representation of a dynamical process. RQA measures quantify meaningful properties of the system (kind of organization, predictability, stability, etc.).
  
-Recurrence analysis is intuitively simple: make a 2D pattern representing “meetings” between time points, a “meeting” occurs when the system is in the same state for both time points. It is also well-grounded in dynamical systems theory (starting from Poincaré recurrence theorem).+Recurrence analysis is intuitively simple: if we conceptualize time as 1D line, we can make a 2D pattern representing “meetings” between points in time, a “meeting” occurs when the system is in the same state for both time points. It is also well-grounded in dynamical systems theory (starting point: [[https://en.wikipedia.org/wiki/Poincar%C3%A9_recurrence_theorem|Poincaré recurrence theorem]]).
  
 **I want to learn RQA, what do I do?** **I want to learn RQA, what do I do?**
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 [[https://www.frontiersin.org/articles/10.3389/fpsyg.2018.02232/full|Cross-recurrence Quantification Analysis in R tutorial]] [[https://www.frontiersin.org/articles/10.3389/fpsyg.2018.02232/full|Cross-recurrence Quantification Analysis in R tutorial]]
  
-Very good, clean and efficient implementation of RQA techniques is part of [[https://juliadynamics.github.io/DynamicalSystems.jl/stable/|DynamicalSystems.jl]] package for Julia (highly recommended).+Very good, clean and efficient implementation of RQA techniques is a part of [[https://juliadynamics.github.io/DynamicalSystems.jl/stable/|DynamicalSystems.jl]] package for Julia (highly recommended).
  
 A comprehensive implementation of most standard recurrence analysis techniques and supplementary heuristics can be found in R in [[https://cran.r-project.org/web/packages/crqa/index.html|cRQA package]]. (Not so efficient for larger volumes of data.) A comprehensive implementation of most standard recurrence analysis techniques and supplementary heuristics can be found in R in [[https://cran.r-project.org/web/packages/crqa/index.html|cRQA package]]. (Not so efficient for larger volumes of data.)
  
 +**Demos**
  
 +RQA plots online: [[https://hill.psych.uw.edu.pl/rqa_js/]]
 +
 +Live RQA demo on human motion (webcam required): [[https://hill.psych.uw.edu.pl/frame_diff_rqa/]]
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 +**Who do I ask for help?**
 +
 +  * [[j.zubek@uw.edu.pl|Julian Zubek]]