Detecting and quantifying causal associations in large nonlinear time series datasets
- Submitting institution
-
The University of East Anglia
- Unit of assessment
- 7 - Earth Systems and Environmental Sciences
- Output identifier
- 185284102
- Type
- D - Journal article
- DOI
-
10.1126/sciadv.aau4996
- Title of journal
- Science Advances
- Article number
- eaau4996
- First page
- -
- Volume
- 5
- Issue
- 11
- ISSN
- 2375-2548
- Open access status
- Deposit exception
- Month of publication
- November
- Year of publication
- 2019
- URL
-
http://www.scopus.com/inward/record.url?scp=85076282481&partnerID=8YFLogxK
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 26
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -