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Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables
The main concept behind causality involves both statistical conditions and temporal relations. However, current approaches to causal inference, focusing on the probability vs. conditional probability contrast, are based on model functions or parametric estimation. These approaches are not appropriat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937367/ https://www.ncbi.nlm.nih.gov/pubmed/27389921 http://dx.doi.org/10.1038/srep29192 |
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author | Yin, Yu Yao, Dezhong |
author_facet | Yin, Yu Yao, Dezhong |
author_sort | Yin, Yu |
collection | PubMed |
description | The main concept behind causality involves both statistical conditions and temporal relations. However, current approaches to causal inference, focusing on the probability vs. conditional probability contrast, are based on model functions or parametric estimation. These approaches are not appropriate when addressing non-stationary variables. In this work, we propose a causal inference approach based on the analysis of Events of Relations (CER). CER focuses on the temporal delay relation between cause and effect, and a binomial test is established to determine whether an “event of relation” with a non-zero delay is significantly different from one with zero delay. Because CER avoids parameter estimation of non-stationary variables per se, the method can be applied to both stationary and non-stationary signals. |
format | Online Article Text |
id | pubmed-4937367 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49373672016-07-13 Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables Yin, Yu Yao, Dezhong Sci Rep Article The main concept behind causality involves both statistical conditions and temporal relations. However, current approaches to causal inference, focusing on the probability vs. conditional probability contrast, are based on model functions or parametric estimation. These approaches are not appropriate when addressing non-stationary variables. In this work, we propose a causal inference approach based on the analysis of Events of Relations (CER). CER focuses on the temporal delay relation between cause and effect, and a binomial test is established to determine whether an “event of relation” with a non-zero delay is significantly different from one with zero delay. Because CER avoids parameter estimation of non-stationary variables per se, the method can be applied to both stationary and non-stationary signals. Nature Publishing Group 2016-07-08 /pmc/articles/PMC4937367/ /pubmed/27389921 http://dx.doi.org/10.1038/srep29192 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Yin, Yu Yao, Dezhong Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title | Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title_full | Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title_fullStr | Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title_full_unstemmed | Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title_short | Causal Inference Based on the Analysis of Events of Relations for Non-stationary Variables |
title_sort | causal inference based on the analysis of events of relations for non-stationary variables |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937367/ https://www.ncbi.nlm.nih.gov/pubmed/27389921 http://dx.doi.org/10.1038/srep29192 |
work_keys_str_mv | AT yinyu causalinferencebasedontheanalysisofeventsofrelationsfornonstationaryvariables AT yaodezhong causalinferencebasedontheanalysisofeventsofrelationsfornonstationaryvariables |