Functional Bayesian networks for discovering causality from multivariate functional data.

Zhou, Fangting; He, Kejun; Wang, Kunbo; Xu, Yanxun; Ni, Yang

Zhou, Fangting; He, Kejun; Wang, Kunbo; Xu, Yanxun; Ni, Yang.

Afiliação

Zhou F; Department of Statistics, Texas A&M University, College Station, Texas, USA.
He K; Center for Applied Statistics, Institute of Statistics and Big Data, Renmin University of China, Beijing, China.
Wang K; Center for Applied Statistics, Institute of Statistics and Big Data, Renmin University of China, Beijing, China.
Xu Y; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA.
Ni Y; Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA.

Biometrics ; 79(4): 3279-3293, 2023 12.

Article em En | MEDLINE | ID: mdl-37635676

Assuntos

Teorema de Bayes; Causalidade; Simulação por Computador; Incerteza

Palavras-chave

causal discovery; directed acyclic graphs; multivariate longitudinal/functional data; non-Gaussianity; structure learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Teorema de Bayes Tipo de estudo: Etiology_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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