Serial Dependence Analysis of Time Series Using Distance Correlation and Monte Carlo Bootstrap Hypothesis Test-Reference-Cited by-同舟云学术

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Serial Dependence Analysis of Time Series Using Distance Correlation and Monte Carlo Bootstrap Hypothesis Test

Published:2023-07-10 Issue: Volume: Page:
ISSN:
Container-title:2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)
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Author:

Koutsellis Themistoklis¹,Choumas Stylianos²,Nikas Alexandros¹,Ververidis Christopher²,Papapolyzos Thomas²,Bitsikas Anastasios³,Makarouni Ioanna¹,Doukas Haris¹

Affiliation:

1. School of Electricaland Computer Engineering National Technical Universityof Athens,Decision Support Systems Laboratory,Athens,Greece

2. HYPERTECH SA,Athens,Greece

3. CAPITAL.GR SA,Athens,Greece

Funder

European Regional Development Fund

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10345839/10345840/10345938.pdf?arnumber=10345938

Reference22 articles.

1. Measuring and testing dependence by correlation of distances

2. Measuring Statistical Dependence with Hilbert-Schmidt Norms

3. Nonlinear system theory: Another look at dependence

4. Hypothesis Testing in Time Series via the Empirical Characteristic Function: A Generalized Spectral Density Approach

5. Measuring nonlinear dependence in time-series, a distance correlation approach

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