Improving partial mutual information-based input variable selection by consideration of boundary issues associated with bandwidth estimation

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dc.contributor.authorLi, X.
dc.contributor.authorZecchin, A.
dc.contributor.authorMaier, H.
dc.date.issued2015
dc.description.abstractAbstract not available
dc.description.statementofresponsibilityXuyuan Li, Aaron C. Zecchin, Holger R. Maier
dc.identifier.citationEnvironmental Modelling and Software, 2015; 71:78-96
dc.identifier.doi10.1016/j.envsoft.2015.05.013
dc.identifier.issn1364-8152
dc.identifier.issn1873-6726
dc.identifier.orcidZecchin, A. [0000-0001-8908-7023]
dc.identifier.orcidMaier, H. [0000-0002-0277-6887]
dc.identifier.urihttp://hdl.handle.net/2440/96957
dc.language.isoen
dc.publisherElsevier
dc.rights© 2015 Elsevier Ltd. All rights reserved.
dc.source.urihttps://doi.org/10.1016/j.envsoft.2015.05.013
dc.subjectArtificial neural networks; Data-driven models; Partial mutual information; Kernel density estimation; Kernel bandwidth; Boundary issues; Hydrology and water resources; Input variable selection
dc.titleImproving partial mutual information-based input variable selection by consideration of boundary issues associated with bandwidth estimation
dc.typeJournal article
pubs.publication-statusPublished

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