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diffusr (version 0.1.4)

Network Diffusion Algorithms

Description

Implementation of network diffusion algorithms such as heat diffusion or Markov random walks. Network diffusion algorithms generally spread information in the form of node weights along the edges of a graph to other nodes. These weights can for example be interpreted as temperature, an initial amount of water, the activation of neurons in the brain, or the location of a random surfer in the internet. The information (node weights) is iteratively propagated to other nodes until a equilibrium state or stop criterion occurs.

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install.packages('diffusr')

Monthly Downloads

58

Version

0.1.4

License

GPL (>= 3)

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Last Published

May 17th, 2018

Functions in diffusr (0.1.4)

nearest.neighbors

Graph diffusion using nearest neighbors
diffusr-package

diffusr
normalize.stochastic

Create a stochastically normalized matrix/vector
heat.diffusion

Graph diffusion using a heat diffusion process on a Laplacian matrix.
normalize.laplacian

Calculate the Laplacian of a matrix
hub.correction

Correct for hubs in an adjacency matrix
random.walk

Graph diffusion using a Markov random walk