[期刊论文]


Causality inference of linearly correlated variables: The statistical simulation and regression method

作   者:
WenJun Zhang;

出版年:2021

页     码:154 - 161
出版社:International Academy of Ecology and Environmental Sciences


摘   要:

Causality inference of variables is a research focus in science. Due to its importance, a statistical simulation and regression method for causality inference of linearly correlated (scale or interval) variables was proposed in present study. First, a statistical simulation and regression method was developed to generate and analyze artificial data of linear correlated variables with known causality. The rule was drawn from the simulation and regression analysis on artificial data. Finally, causality inference of two linearly correlated variables was conducted based on the rule. Full Matlab codes of the method were presented.



关键字:

causality ; inference ; linear dependency ; scale or interval variables ; Pearson correlation ; statistical simulation ; regression analysis


全文
所属期刊
Computational Ecology and Software
ISSN:
来自:International Academy of Ecology and Environmental Sciences