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 returns a network
object whose edgeset reflects the given information. 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 an adjacency matrix where the rows are thge actors and the columns are the 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
.
An object of class network
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. 2002. ``Memory Structures for Relational Data in R: Classes and Interfaces'' Working Paper.
network
, network.initialize
, add.edge
#Create an arbitrary adjacency matrix m<-matrix(rbinom(25,1,0.5),5,5) diag(m)<-0 g<-network.initialize(5) #Initialize the network g<-network.adjacency(m,g) #Import the edge data