| pfvn {multiplex} | R Documentation |
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)
Arguments
x |
network data, typically valued |
r |
a distance function parameter |
q |
parameter with the minimum distance between actors in the proximity matrix |
Details
The Pathfinder structure is for undirected networks, whereas for directed network structures the triangle inequality principle is applied
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 |
Author(s)
Antonio Rivero Ostoic
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, John Wiley & Sons. 2014.
See Also
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)