Cargando…
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: | Yin, Yu, Yao, Dezhong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
|
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 |
Ejemplares similares
-
A new method of Bayesian causal inference in non-stationary environments
por: Shinohara, Shuji, et al.
Publicado: (2020) -
Causal inference: relating language to event representations and events in the world
por: Wei, Yipu, et al.
Publicado: (2023) -
Network inference from non-stationary spike trains
por: Tyrcha, Joanna, et al.
Publicado: (2011) -
Matlab Open Source Code: Noise-Assisted Multivariate Empirical Mode Decomposition Based Causal Decomposition for Causality Inference of Bivariate Time Series
por: Zhang, Yi, et al.
Publicado: (2022) -
The Role of Instrumental Variables in Causal Inference Based on Independence of Cause and Mechanism
por: Sokolovska, Nataliya, et al.
Publicado: (2021)