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dc.contributor.authorSpencer, Christopher J.
dc.contributor.authorYakymchuk, Chris
dc.contributor.authorGhaznavi, Mahmoudreza
dc.date.accessioned2018-05-18 15:29:51 (GMT)
dc.date.available2018-05-18 15:29:51 (GMT)
dc.date.issued2017-11-01
dc.identifier.urihttp://dx.doi.org/10.1016/j.gsf.2017.05.002
dc.identifier.urihttp://hdl.handle.net/10012/13324
dc.description.abstractThe application of frequency distribution statistics to data provides objective means to assess the nature of the data distribution and viability of numerical models that are used to visualize and interpret data. Two commonly used tools are the kernel density estimation and reduced chi-squared statistic used in combination with a weighted mean. Due to the wide applicability of these tools, we present a Java-based computer application called KDX to facilitate the visualization of data and the utilization of these numerical tools.en
dc.description.sponsorshipChina University of Geosciences (Beijing)en
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectData visualisationen
dc.subjectKernel density estimationen
dc.subjectReduced chi-squared statisticen
dc.subjectMean square weighted deviationen
dc.subjectGeostatisticsen
dc.titleVisualising data distributions with kernel density estimation and reduced chi-squared statisticen
dc.typeArticleen
dcterms.bibliographicCitationSpencer, C. J., Yakymchuk, C., & Ghaznavi, M. (2017). Visualising data distributions with kernel density estimation and reduced chi-squared statistic. Geoscience Frontiers, 8(6), 1247–1252. doi:10.1016/j.gsf.2017.05.002en
uws.contributor.affiliation1Faculty of Scienceen
uws.contributor.affiliation2Earth and Environmental Sciencesen
uws.typeOfResourceTexten
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


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