Measurement of Linear Dependence and Feedback between Multiple Time Series
Abstract
Measures of linear dependence and feedback for multiple time series are defined. The measure of linear dependence is the sum of the measure of linear feedback from the first series to the second, linear feedback from the second to the first, and instantaneous linear feedback. The measures are nonnegative, and zero only when feedback (causality) of the relevant type is absent. The measures of linear feedback from one series to another can be additively decomposed by frequency. A readily usable theory of inference for all of these measures and their decompositions is described; the computations involved are modest.
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Causality or directionality is often inferred from time series: if past activity in A predicts current or future activity in B, A causes or drives B through a connectivity pointing from A to B.
“Causality or directionality is often inferred from time series: if the past activity in A predicts the current or future activity in B, A causes or drives B through a connectivity pointing from A to B (96).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [96]
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- Authors
- Geweke, J.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Geweke, John
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1982-06
- Volume
- 77
- Issue
- 378
- Pages
- 304-313
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2025371899
- Cited by
- 2,060
- References
- 20
- Citations by year
- 2026: 67 · 2025: 88 · 2024: 80 · 2023: 126 · 2022: 139 · 2021: 147 · 2020: 127 · 2019: 101 · 2018: 102 · 2017: 86 · 2016: 99 · 2015: 102 · 2014: 82 · 2013: 91 · 2012: 71
- FWCI
- 40.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the American Statistical Association (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
- Keywords
- linear dependence, linear feedback, multiple time series, causality, real-time feedback, frequency decomposition
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