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EMMAgeo - R package

Cite as:

Dietze, Elisabeth; Dietze, Michael (2019): EMMAgeo - R package. V. 0.9.6. GFZ Data Services. http://doi.org/10.5880/GFZ.4.6.2019.002

Status

I   N       R   E   V   I   E   W : Dietze, Elisabeth; Dietze, Michael (2019): EMMAgeo - R package. V. 0.9.6. GFZ Data Services. http://doi.org/10.5880/GFZ.4.6.2019.002

Abstract

EMMA – End Member Modelling Analysis of grain-size data is a technique to unmix multimodal grain-size data sets, i.e., to decompose the data into the underlying grain-size distributions (loadings) and their contributions to each sample (scores). The R package EMMAgeo contains a series of functions to perform EMMA based on eigenspace decomposition. The data are rescaled and transformed to receive results in meaningful units, i.e., volume percentage. EMMA can be performed in a deterministic and two robust ways, the latter taking into account incomplete knowledge about model parameters. The model outputs can be interpreted in terms of sediment sources, transport pathways and transport regimes (loadings) as well as their relative importance throughout the sample space (scores).

Contact

  • Dietze, Elisabeth (Researcher) ; Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany;

Keywords

environment > natural environment > marine environment, environment > natural environment > terrestrial environment, Sedimentology, grain-size, unmixing, decomposition, EMMA, end-member, modelling, proxy

GCMD Science Keywords

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          • givenName: Elisabeth
          • familyName: Dietze
          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0003-4817-8441
          • affiliation: Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
          • affiliation: AWI
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          • affiliation: GFZ German Research Centre for Geosciences, Potsdam, Germany
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      • publisher: GFZ Data Services
      • publicationYear: 2019
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        • subject: grain-size
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        • subject: decomposition
        • subject: EMMA
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        • subject: modelling
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        • subject (schemeURI=http://www.eionet.europa.eu/gemet/ subjectScheme=GEMET xml:lang=en): environment > natural environment > terrestrial environment
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          • givenName: Elisabeth
          • familyName: Dietze
          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0003-4817-8441
          • affiliation: Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
          • affiliation: AWI
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          • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-6063-1726
          • affiliation: GFZ German Research Centre for Geosciences, Potsdam, Germany
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      • version: 0.9.6
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        • description (descriptionType=Abstract): EMMA – End Member Modelling Analysis of grain-size data is a technique to unmix multimodal grain-size data sets, i.e., to decompose the data into the underlying grain-size distributions (loadings) and their contributions to each sample (scores). The R package EMMAgeo contains a series of functions to perform EMMA based on eigenspace decomposition. The data are rescaled and transformed to receive results in meaningful units, i.e., volume percentage. EMMA can be performed in a deterministic and two robust ways, the latter taking into account incomplete knowledge about model parameters. The model outputs can be interpreted in terms of sediment sources, transport pathways and transport regimes (loadings) as well as their relative importance throughout the sample space (scores).
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      • Entry_Title: EMMAgeo - R package
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        • Dataset_Title: EMMAgeo - R package
        • Dataset_Release_Date: 2019
        • Dataset_Release_Place: Potsdam, Germany
        • Dataset_Publisher: GFZ Data Services
        • Online_Resource: http://dx.doi.org/10.5880/GFZ.4.6.2019.002
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        • Topic: DATA ANALYSIS AND VISUALIZATION
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      • Parameters
        • Category: EARTH SCIENCE
        • Topic: CLIMATE INDICATORS
        • Term: PALEOCLIMATE INDICATORS
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        • Topic: PALEOCLIMATE
        • Term: LAND RECORDS
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        • Topic: PALEOCLIMATE
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        • Topic: LAND SURFACE
        • Term: GEOMORPHOLOGY
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      • Keyword: environment > natural environment > marine environment
      • Keyword: environment > natural environment > terrestrial environment
      • Keyword: Sedimentology
      • Keyword: grain-size
      • Keyword: unmixing
      • Keyword: decomposition
      • Keyword: EMMA
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      • Keyword: modelling
      • Keyword: proxy
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          • Long_Name: GFZ
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          • Last_Name: Deutsches GeoForschungsZentrum GFZ
      • Summary
        • Abstract: EMMA – End Member Modelling Analysis of grain-size data is a technique to unmix multimodal grain-size data sets, i.e., to decompose the data into the underlying grain-size distributions (loadings) and their contributions to each sample (scores). The R package EMMAgeo contains a series of functions to perform EMMA based on eigenspace decomposition. The data are rescaled and transformed to receive results in meaningful units, i.e., volume percentage. EMMA can be performed in a deterministic and two robust ways, the latter taking into account incomplete knowledge about model parameters. The model outputs can be interpreted in terms of sediment sources, transport pathways and transport regimes (loadings) as well as their relative importance throughout the sample space (scores).
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        • givenName: Elisabeth
        • familyName: Dietze
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0003-4817-8441
        • affiliation: Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
        • affiliation: AWI
      • creator
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        • givenName: Michael
        • familyName: Dietze
        • nameIdentifier (nameIdentifierScheme=ORCID): 0000-0001-6063-1726
        • affiliation: GFZ German Research Centre for Geosciences, Potsdam, Germany

Files

License

GNU General Public License, Version 3, 29 June 2007, Copyright © 2019 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences (E. & M. Dietze)