Characterization of autoregressive processes using entropic quantifiers

DOI10.1016/j.physa.2017.07.025OpenAlexW2739670369MaRDI QIDQ2149969

Francisco O. Redelico, Francisco Traversaro

Publication date: 27 June 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11336/93004

zbMATH Keywords

time series analysispermutation entropy

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Cites Work

• Permutation entropy of fractional Brownian motion and fractional Gaussian noise
• A limit theorem for the maximum of autoregressive processes with uniform marginal distributions
• Multiscale behaviour of volatility autocorrelations in a financial market
• Contrasting chaos with noise via local versus global information quantifiers
• GENERALIZED STATISTICAL COMPLEXITY MEASURE
• A new autoregressive time series model in exponential variables (NEAR(1))
• Uniformly distributed first-order autoregressive time series models and multiplicative congruential random number generators
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Science from Fisher Information

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