Mutual information: a measure of dependency for nonlinear time series
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Previous studies on mental health relied on the mutual information (MI) method from information theory.
“Instead of correlations, previous studies on mental health relied on the mutual information (MI) method from Information theory [87-89].”
The mutual information (MI) method measures both linear and nonlinear statistical dependencies between variables.
“The advantage of using the MI method is that the MI measures both linear and nonlinear statistical dependencies between variables.”
Correlation coefficients only measure the extent of the linear relationship between variables.
“Moreover, correlation coefficients only measure the extent of the linear relationship between variables [87,88].”
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References 7 · Cited by 213
- Authors
- Dionisio, A., Menezes, R., & Mendes, D. A.
- Affiliations
- Iscte – Instituto Universitário de Lisboa (PT)
- Venue
- Physica A: Statistical Mechanics and its Applications
- Publisher
- Elsevier BV
- Published
- 2004-12
- Volume
- 344
- Issue
- 1-2
- Pages
- 326-329
- ISSN
- 0378-4371 (ISSN-L)
- OpenAlex
- W2073190199
- Cited by
- 213
- References
- 7
- Citations by year
- 2026: 10 · 2025: 14 · 2024: 14 · 2023: 14 · 2022: 29 · 2021: 12 · 2020: 14 · 2019: 12 · 2018: 9 · 2017: 12 · 2016: 7 · 2015: 12 · 2014: 11 · 2013: 6 · 2012: 11
- FWCI
- 2.38
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Physica A Statistical Mechanics and its Applications (publishedVersion)
- Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Statistical Mechanics and Entropy
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Keywords
- mutual information, nonlinear dependence, financial time series, dependence measures, nonlinear time series, nonparametric estimation
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