Comparer des méthodes

	Entropy d'échantillon	Analyse de Quantification de Récurrence (AQR)
Domaine	Systèmes complexes	Systèmes complexes
Famille	Machine learning	Machine learning
Année d'origine	2000	2007
Auteur d'origine	Richman & Moorman	Marwan, Romano, Thiel & Kurths
Type	Nonlinear entropy measure	Nonlinear time-series characterization
Source fondatrice	Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology, 278(6), H2039–H2049.	Marwan, N., Romano, M. C., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5–6), 237–329.
Alias	SampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure	RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi
Apparentées	2	2
Résumé	Sample Entropy (SampEn) is a nonlinear measure of the complexity and regularity of a time series. Introduced by Richman and Moorman in 2000 as an improvement over Approximate Entropy (ApEn), it quantifies the likelihood that similar patterns of a given length in the series remain similar when extended by one additional data point. A higher SampEn value indicates greater irregularity and complexity, while a lower value indicates more regularity or self-similarity.	Recurrence Quantification Analysis (RQA) is a nonlinear method for characterizing the dynamics of a time series by quantifying the small-scale structure of its recurrence plot. Introduced in its modern, comprehensive form by Marwan, Romano, Thiel, and Kurths in 2007, RQA extracts scalar measures — such as recurrence rate, determinism, laminarity, and Shannon entropy — that capture periodicity, chaos, stationarity, and transitions in complex dynamical systems.