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Description

Probabilistic Numerical Modelling of Sediment Properties.

A flexible framework for definition and application of time/depth- based rules for sets of parameters for single grains that can be used to create artificial sediment profiles. Such profiles can be used for virtual sample preparation and synthetic, for instance, luminescence measurements.

sandbox

Creating and analysing synthetic sediment sections with R

Project Status: Active – The project has reached a stable, usablestate and is being activelydeveloped. CRAN

Installation

To install the latest development builds directly from GitHub, run

if(!require("devtools"))
  install.packages("devtools")
devtools::install_github("coffeemuggler/sandbox@<wanted branch>")

License

License: GNU General Public License, Version 3, 29 June 2007

Copyright © 2021 coffeemuggler developers community

sandbox is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. sandbox is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

Citation

Please use both of the below references when citing the usage of the package. It is important to not just use one of them but the two.

Dietze, M., Kreutzer, S. (2021): sandbox - an R tool for creating and analysing synthetic sediment sections. V. 0.2.0. GFZ Data Services. https://doi.org/10.5880/GFZ.4.6.2021.005

Dietze, M., Kreutzer, S., Fuchs, M. C., and Meszner, S.: sandbox – Creating and Analysing Synthetic Sediment Sections with R, Geochronology Discuss. [preprint], https://doi.org/10.5194/gchron-2021-39, in review, 2021.

Funding

Sebastian Kreutzer received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 844457 (project: CREDit).

Metadata

Version

0.2.1

License

Unknown

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