Assessing serial dependence in ordinal patterns processes using chi-squared tests with application to EEG data analysis

DOI10.1063/5.0096954MaRDI QIDQ6565134

Jaroslav Hlinka, Arthur Matsuo Yamashita Rios de Sousa

Publication date: 1 July 2024

Published in: Chaos (Search for Journal in Brave)

Mathematics Subject Classification ID

Inference from stochastic processes (62Mxx) Nonparametric inference (62Gxx) Sufficiency and information (62Bxx)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A non-parametric independence test using permutation entropy
• Permutation entropy and its main biomedical and econophysics applications: a review
• A non-parametric test for independence based on symbolic dynamics
• Detection of non-linear structure in time series
• Computing a nearest symmetric positive semidefinite matrix
• Non-parametric analysis of serial dependence in time series using ordinal patterns
• Using permutations to detect dependence between time series
• Transcripts: An algebraic approach to coupled time series
• Ordinal symbolic analysis and its application to biomedical recordings
• A symbolic test for testing independence between time series
• Order Patterns in Time Series
• A Dual Approach to Semidefinite Least-Squares Problems
• A Dependence Metric for Possibly Nonlinear Processes
• The modified permutation entropy-based independence test of time series
• The Relation Between Measures of Correlation in the Universe of Sample Permutations

Related Items (4)

Ordinal methods: concepts, applications, new developments, and challenges -- in memory of Karsten Keller (1961--2022) ⋮ Sign patterns symbolization and its use in improved dependence test for complex network inference ⋮ The asymptotic distribution of the permutation entropy ⋮ Statistics and contrasts of order patterns in univariate time series

This page was built for publication: Assessing serial dependence in ordinal patterns processes using chi-squared tests with application to EEG data analysis