Data Publications

EMMAgeo - R package

hasData_Center_Short_Name
  • Deutsches GeoForschungsZentrum GFZ
hasDataset_Online_Resource
hasDataset_Release_Date
  • 2019
hasDataset_Title
  • EMMAgeo - R package
hasEntry_ID
  • 10.5880/GFZ.4.6.2019.002
hasKeyword
  • modelling
  • unmixing
  • environment > natural environment > terrestrial environment
  • EMMA
  • Sedimentology
  • decomposition
  • end-member
  • grain-size
  • proxy
  • environment > natural environment > marine environment
hasSummary
  • 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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