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ОбластьЭконометрикаСложные системы
СемействоRegression modelMachine learning
Год появления19692000
Автор методаClive W. J. GrangerRichman & Moorman
ТипTime-series predictive causality testNonlinear entropy measure
Основополагающий источникGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗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. DOI ↗
Другие названияGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiSampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure
Связанные52
СводкаThe Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.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.
ScholarGateНабор данных
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ScholarGateСравнение методов: Granger Causality · Sample Entropy. Получено 2026-06-18 из https://scholargate.app/ru/compare