1. Repositório PUCRS
  2. PUBLICAÇÕES CIENTÍFICAS
  3. Artigo de Periódico
Please use this identifier to cite or link to this item: https://hdl.handle.net/10923/20653
Full metadata record
DC FieldValueLanguage
dc.contributor.authorCARVALHO, ELIAS CESAR ARAUJO DE-
dc.contributor.authorVISSOCI, JOAO RICARDO NICKENIG-
dc.contributor.authorANDRADE, LUCIANO DE-
dc.contributor.authorWagner de Lara Machado-
dc.contributor.authorPARAISO, EMERSON CABRERA-
dc.contributor.authorNIEVOLA, JULIO CESAR-
dc.date.accessioned2021-12-22T14:09:24Z-
dc.date.available2021-12-22T14:09:24Z-
dc.date.issued2021-
dc.identifier.issn0950-7051-
dc.identifier.urihttps://hdl.handle.net/10923/20653-
dc.language.isoen-
dc.relation.ispartofKNOWLEDGE-BASED SYSTEMS-
dc.rightsopenAccess-
dc.titleBNPA: An R package to learn path analysis input models from a data set semi-automatically using Bayesian networks-
dc.typeArticle-
dc.date.updated2021-12-22T14:09:23Z-
dc.identifier.doiDOI:10.1016/j.knosys.2021.107042-
dc.jtitleKNOWLEDGE-BASED SYSTEMS-
dc.volume223-
dc.spage107042-
Appears in Collections:Artigo de Periódico

Files in This Item:
File Description SizeFormat 
BNPA_An_R_package_to_learn_path_analysis_input_models_from_a_data_set_semiautomatically_using_Bayesian_networks.pdf2,92 MBAdobe PDFOpen
View
Show simple item record See statistics Search for other versions of fulltext via SFX


All Items in PUCRS Repository are protected by copyright, with all rights reserved, and are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Read more.