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eRTG3D  

Empirically Informed Random Trajectory Generation in 3-D
View on CRAN: Click here


Download and install eRTG3D package within the R console
Install from CRAN:
install.packages("eRTG3D")

Install from Github:
library("remotes")
install_github("cran/eRTG3D")

Install by package version:
library("remotes")
install_version("eRTG3D", "0.7.0")



Attach the package and use:
library("eRTG3D")
Maintained by
Merlin Unterfinger
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-09-19
Latest Update: 2022-02-25
Description:
Creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories. Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. . Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. .
How to cite:
Merlin Unterfinger (2019). eRTG3D: Empirically Informed Random Trajectory Generation in 3-D. R package version 0.7.0, https://cran.r-project.org/web/packages/eRTG3D. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:34), 0.6.2 (2019-09-19 18:20), 0.6.3 (2020-07-27 01:10), 0.6.4 (2021-10-02 17:10)
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Complete documentation for eRTG3D
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