| edgeset.constructors {network} | R Documentation |
These functions convert relational data in matrix form to network edge sets.
network.adjacency(x, g, ignore.eval = TRUE, names.eval = NULL, ...) network.edgelist(x, g, ignore.eval = TRUE, names.eval = NULL, ...) network.incidence(x, g, ignore.eval = TRUE, names.eval = NULL, ...) network.bipartite(x, g, ignore.eval = TRUE, names.eval = NULL, ...)
x |
a matrix containing edge information |
g |
an object of class network |
ignore.eval |
logical; ignore edge values? |
names.eval |
the edge attribute under which to store edge values, if any |
... |
additional arguments to add.edge |
Each of the above functions takes a network and a matrix as input, and modifies the supplied network object by adding the appropriate edges. network.adjacency takes x to be an adjacency matrix; code.edgelist takes x to be an edgelist matrix; and network.incidence takes x to be an incidence matrix. network.bipartite takes x to be a two-mode adjacency matrix where rows and columns reflect each respective mode (conventionally, actors and events); If ignore.eval==FALSE, (non-zero) edge values are stored as edgewise attributes with name names.eval. Any additional command line parameters are passed to add.edge.
Results similar to network.adjacency can also be obtained by means of extraction/replacement operators. See the associated man page for details.
Invisibly, an object of class network; these functions modify their argument in place.
Handling of missing data is not yet fully implemented.
Carter T. Butts buttsc@uci.edu and David Hunter dhunter@stat.psu.edu
Butts, C. T. (2008). “network: a Package for Managing Relational Data in R.” Journal of Statistical Software, 24(2). http://www.jstatsoft.org/v24/i02/
network, network.initialize, add.edge, network.extraction
#Create an arbitrary adjacency matrix m<-matrix(rbinom(25,1,0.5),5,5) diag(m)<-0 g<-network.initialize(5) #Initialize the network network.adjacency(m,g) #Import the edge data #Do the same thing, using replacement operators g<-network.initialize(5) g[,]<-m