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dc.contributor.authorPolanco-Martínez, J.M.
dc.date.accessioned2024-02-05T11:51:24Z
dc.date.available2024-02-05T11:51:24Z
dc.date.issued2023-05-01
dc.identifier.citationSoftware Impacts: 16: 100514 (2023)es_ES
dc.identifier.urihttp://hdl.handle.net/10810/64633
dc.description.abstractThe R package VisualDom estimates and plots the correlation coefficients obtained via the wavelet local multiple correlation and the variables that maximizes the wavelet multiple correlation through time and scale, i.e. the “dominant” variables of a dynamical system. The novel graphical tool to find out dominant variables that we are proposing is able to obtain knowledge from diverse types of dynamical systems, e.g. the climate system. The functions included in VisualDom are quite flexible because these contain multiple parameters for controlling the plot of the time series under analysis and the heat maps of the correlation coefficients and dominant variables.es_ES
dc.description.sponsorshipJMPM acknowledges to the Excellence Unit GECOS (reference number CLU-2019-03), Universidad de Salamanca for funding support.es_ES
dc.language.isoenges_ES
dc.publisherSoftware Impactses_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/*
dc.subjectDynamic wavelet correlationes_ES
dc.subjectDynamical systemses_ES
dc.subjectMODWTes_ES
dc.subjectMulti-scale phenomenaes_ES
dc.subjectNonlinear dynamicses_ES
dc.subjectWavelet multiple correlationes_ES
dc.titleVisualDom: An R package for estimating dominant variables in dynamical systems[Formula presented]es_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2023 The Author(s).es_ES
dc.rights.holderAtribución-NoComercial-CompartirIgual 3.0 España*
dc.relation.publisherversionhttps://dx.doi.org/10.1016/j.simpa.2023.100514es_ES
dc.identifier.doi10.1016/j.simpa.2023.100514


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