Analytical Methods for Stream DAGs
Overview
Provides indices and tools for directed acyclic graphs (DAGs), particularly DAG representations of intermittent streams. A detailed introduction to the package can be found in the publication: "Non-perennial stream networks as directed acyclic graphs: The R-package streamDAG" (Aho et al., 2023) doi:10.1016/j.envsoft.2023.105775, and in the introductory package vignette.
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 50
- Examples that run
- 100%31 run in a plain check
- Exported functions with examples
- 94%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 30%
Downloads
Dependencies
Installing streamDAG adds 35 packages (17 with compiled code, 21 MB of source tarballs). Heaviest: igraph 4.8 MB, asbio 1.9 MB, deSolve 1.9 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2023-08-21
- Total releases
- 4 / 3 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 4.0
- Bundled data
- 98 KB / 20 files
- Download size
- 2.5 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("streamDAG")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.