Analytical Methods for Stream DAGs
Raise an adjacency matrix to some power
Arcs of a directed graph
Obtain arc stream activity outcomes based on bounding nodes
Assortativity
Botter and Durighetto Bernoulli stream length
Posterior Beta and Inverse-beta summaries
Bivariate Bernoulli Distribution
Potential degree distributions
Delete arcs based on presence absence data
Delete nodes based on presence absence data
Inverse Beta Distribution
Local and global efficiency
Loads AIMS dataset associated with a particular AIMS graph
Global Summary
Harary Index
Generalized DAG indices
Integral connectivity scale length (ICSL)
Improved Closeness Centrality
Size of intact network that feeds into the sink or a particular node
Detects and defines islands in a streamDAG
Coordinates of nodes in the Konza Praire dataset
local (nodal) summaries of a DAG
Path Visibilities
Identify source and sink nodes
Path Lengths
Plot degree distributions
Bounds for the correlation of two (or more) Benrnoulli random variable...
Size of the intact network above an arc
Shortest path lengths and number of paths
Spatial plot of an igraph object or stream shapefile
A wrapper for missForest for random forest STIC imputation
Strahler or Shreve stream order of a stream DAG
Stream DAG datasets
Functions for overlaying networks on shapefiles
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.