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      Kernel density estimation and transition maps of Moldavian Neolithic and Eneolithic settlement

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      Data in Brief
      Elsevier

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          Abstract

          The data presented in this article are related to the research article entitled “Neo-Eneolithic settlement pattern and salt exploitation in Romanian Moldavia” (Brigand and Weller, 2018) [1]. Kernel density estimation (KDE) is used in order to move beyond the discrete distribution of sites and to enable us to work on a continuous surface that reflects the intensity of the occupation in the space. Maps of density per period – Neolithic I (Cris), Neolithic II (LBK), Eneolithic I (Precucuteni), Eneolithic II (Cucuteni A), Eneolithic III-IV (Cucuteni A-B and B) – are used to create maps of density difference (Figs. 1–4) in order to analyse the dynamic (either non-existent, negative or positive) between two chronological sequences.

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          Some Archaeological Applications of Kernel Density Estimates

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            Choosing the window width when estimating a density

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              Neo-Eneolithic settlement pattern and salt exploitation in Romanian Moldavia

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                Author and article information

                Contributors
                Journal
                Data Brief
                Data Brief
                Data in Brief
                Elsevier
                2352-3409
                03 February 2018
                April 2018
                03 February 2018
                : 17
                : 452-458
                Affiliations
                [0005]UMR 8215 (Trajectoires), CNRS & Univ. Paris-I Panthéon Sorbonne, France
                Author notes
                Article
                S2352-3409(18)30054-4
                10.1016/j.dib.2018.01.051
                5988340
                94e73512-b6f2-461d-a74d-3c6a8ca9e933
                © 2018 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 October 2017
                : 11 January 2018
                : 18 January 2018
                Categories
                Social Science

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