eRTG3D

cranv0.7.0

Empirically Informed Random Trajectory Generation in 3-D. 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 movem

License GPL-3strong copyleft0 versions1 maintainers7 deps96 weekly dl
munterfi/eRTG3D/
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  • Low health score (36/100)
Health breakdown0 – 100
0/25
maintenance
0/20
popularity
25/25
security
9/15
maturity
2/15
community
Vulnerabilities
0
none known

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Dependencies (7)
CircStatsggplot2pbapplyplotlyrasterrasterVistiff
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First published · 2022-02-25 13:08:30

Last updated · 2022-02-25T11:10:05+00:00

eRTG3D — Health Score 36/100 | DepScope