A statistical simulation method for causality inference of Boolean variables

In present study, a statistical simulation method for causality inference of Boolean variables was proposed. First, I used statistical simulation to generate artificial data of two Boolean variables with known independent and dependent variables. A law was drawn from the simulation analysis of the a...

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Autor principal: WenJun Zhang
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Lenguaje:EN
Publicado: International Academy of Ecology and Environmental Sciences 2021
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Acceso en línea:https://doaj.org/article/8b6fe77a115f49c19b5a03dd3554c5c6
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spelling oai:doaj.org-article:8b6fe77a115f49c19b5a03dd3554c5c62021-11-17T03:21:54ZA statistical simulation method for causality inference of Boolean variables2220-8879https://doaj.org/article/8b6fe77a115f49c19b5a03dd3554c5c62021-12-01T00:00:00Zhttp://www.iaees.org/publications/journals/nb/articles/2021-11(4)/a-method-for-causality-inference-of-Boolean-variables.pdfhttps://doaj.org/toc/2220-8879In present study, a statistical simulation method for causality inference of Boolean variables was proposed. First, I used statistical simulation to generate artificial data of two Boolean variables with known independent and dependent variables. A law was drawn from the simulation analysis of the artificial data. For a set of data of two Boolean variables, a randomization method was proposed and used to test the statistical significance of the Boolean correlation measure (point correlation, quartile correlation, or Jaccard correlation, etc.). The causality inference was then conducted to observed data based on the law. Finally, the statistical simulation was used to determine the statistic significance of the causality. Full Matlab codes were presented also.WenJun ZhangInternational Academy of Ecology and Environmental Sciencesarticlecausalityinferencecorrelationpoint correlationjaccardboolean variablesrandomizationstatistical simulationmachine learningartificial intelligenceindependent variablecausal inferenceBiology (General)QH301-705.5ENNetwork Biology, Vol 11, Iss 4, Pp 263-273 (2021)
institution DOAJ
collection DOAJ
language EN
topic causality
inference
correlation
point correlation
jaccard
boolean variables
randomization
statistical simulation
machine learning
artificial intelligence
independent variable
causal inference
Biology (General)
QH301-705.5
spellingShingle causality
inference
correlation
point correlation
jaccard
boolean variables
randomization
statistical simulation
machine learning
artificial intelligence
independent variable
causal inference
Biology (General)
QH301-705.5
WenJun Zhang
A statistical simulation method for causality inference of Boolean variables
description In present study, a statistical simulation method for causality inference of Boolean variables was proposed. First, I used statistical simulation to generate artificial data of two Boolean variables with known independent and dependent variables. A law was drawn from the simulation analysis of the artificial data. For a set of data of two Boolean variables, a randomization method was proposed and used to test the statistical significance of the Boolean correlation measure (point correlation, quartile correlation, or Jaccard correlation, etc.). The causality inference was then conducted to observed data based on the law. Finally, the statistical simulation was used to determine the statistic significance of the causality. Full Matlab codes were presented also.
format article
author WenJun Zhang
author_facet WenJun Zhang
author_sort WenJun Zhang
title A statistical simulation method for causality inference of Boolean variables
title_short A statistical simulation method for causality inference of Boolean variables
title_full A statistical simulation method for causality inference of Boolean variables
title_fullStr A statistical simulation method for causality inference of Boolean variables
title_full_unstemmed A statistical simulation method for causality inference of Boolean variables
title_sort statistical simulation method for causality inference of boolean variables
publisher International Academy of Ecology and Environmental Sciences
publishDate 2021
url https://doaj.org/article/8b6fe77a115f49c19b5a03dd3554c5c6
work_keys_str_mv AT wenjunzhang astatisticalsimulationmethodforcausalityinferenceofbooleanvariables
AT wenjunzhang statisticalsimulationmethodforcausalityinferenceofbooleanvariables
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