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Evaluating Directed Acyclic Graphs with DAGMetrics: Insights from Tuber and Soil Microbiome Data

Understanding and evaluating directed acyclic graphs (DAGs) is crucial for causal discovery, particularly in high-dimensional and small-sample datasets such as microbial abundance data. This study introduces DAGMetrics, an R package designed to comprehensively evaluate and compare DAGs. The package...

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Principais autores: Pavel Averin, Ifigeneia Mellidou, Maria Ganopoulou, Aliki Xanthopoulou, Theodoros Moysiadis
Formato: Artigo
Idioma:Inglês
Publicado em: MDPI AG 2025-04-01
coleção:Agronomy
Assuntos:
agronomic data analysis
Bayesian networks
causal discovery
directed acyclic graphs
Markov blanket
metagenomics
Acesso em linha:https://www.mdpi.com/2073-4395/15/4/987
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