CLC number:
On-line Access: 2022-05-24
Received: 2022-04-21
Revision Accepted: 2022-05-05
Crosschecked: 0000-00-00
Cited: 0
Clicked: 85
Aiguo WANG, Li LIU, Jiaoyun YANG, Lian LI. Causality fields in nonlinear causal effect analysis[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="Causality fields in nonlinear causal effect analysis",
author="Aiguo WANG, Li LIU, Jiaoyun YANG, Lian LI",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2200165"
}
%0 Journal Article
%T Causality fields in nonlinear causal effect analysis
%A Aiguo WANG
%A Li LIU
%A Jiaoyun YANG
%A Lian LI
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2200165
TY - JOUR
T1 - Causality fields in nonlinear causal effect analysis
A1 - Aiguo WANG
A1 - Li LIU
A1 - Jiaoyun YANG
A1 - Lian LI
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2200165
Abstract: Compared with linear causality, nonlinear causality has more complex characteristics and content. This paper discusses certain issues related to nonlinear causality with an emphasis on the concept of causality field. Based on widely used computation models and methods, some viewpoints and opinions are presented on the analysis and computation of nonlinear causality and the identification problem of causality fields. Besides, via several specific examples, this paper reveals the importance and practical significance of nonlinear causality in handling complex causal inference problems.
Open peer comments: Debate/Discuss/Question/Opinion
<1>