multiplex (version 3.7)

pfvn: Pathfinder Valued Networks and Triangle Inequality

Description

A function to establish the skeleton of a valued network with the pathfinder algorithm and triangle inequality

Usage

pfvn(x, r, q)

Value

max

max value of the network with the Frobenius norm

r

parameter r

q

parameter q

Q

salient structure of x

Note

A note when triangle inequality is used

Arguments

x

network data, typically valued

r

a distance function parameter

q

parameter with the minimum distance between actors in the proximity matrix

Author

Antonio Rivero Ostoic

Details

The Pathfinder structure is for undirected networks, whereas for directed network structures the triangle inequality principle is applied

References

Schvaneveldt, R., Durso, F. and Dearholt, D., “Network structures in proximity data,” in G. Bower, ed., The psychology of learning and motivation: Advances in research & theory, Vol. 24, Academic Press, pp. 249-284. 1989.

Batagelj, V., Doreian, P., Ferligoj, A. and Kejzar, N., Understanding Large Temporal Networks and Spatial Networks: Exploration, Pattern Searching, Visualization and Network Evolution, Wiley. 2014.

See Also

multigraph,

Examples

# create valued network data
arr <- round( array(runif(18), c(3,3,2)), array(runif(18), c(3,3,2)) ) * 10L

# pathfinder valued network of 'arr'
pfvn(arr)