| update.network {ergm} | R Documentation |
Replaces the edges in a network object with the edges corresponding
to the sociomatrix or edge list specified by new.
## S3 method for class 'network' update(object, ...) update_network(object, new, ...) ## S3 method for class 'matrix_edgelist' update_network(object, new, attrname = if (ncol(new) > 2) names(new)[3], ...) ## S3 method for class 'data.frame' update_network(object, new, attrname = if (ncol(new) > 2) names(new)[3], ...) ## S3 method for class 'matrix' update_network(object, new, matrix.type = NULL, attrname = NULL, ...) ## S3 method for class 'ergm_state' update_network(object, new, ...)
object |
a |
... |
Additional arguments; currently unused. |
new |
Either an adjacency matrix (a matrix of values indicating the presence and/or the value of a tie from i to j) or an edge list (a two-column matrix listing origin and destination node numbers for each edge, with an optional third column for the value of the edge). |
attrname |
For a network with edge weights gives the name of the edge attribute whose names to set. |
matrix.type |
One of |
A new network object with the edges specified by
new and network and vertex attributes copied from
the input network object. Input network is not modified.
update_network: dispatcher for network update based on the type of updating information.
update_network.matrix_edgelist: a method for updating a network based on a matrix-form edgelist
update_network.data.frame: a method for updating a network based on an edgelist
update_network.matrix: a method for updating a network based on a matrix
update_network.ergm_state: a method for updating a network based on an ergm_state object.
# data(florentine) # # test the network.update function # # Create a Bernoulli network rand.net <- network(network.size(flomarriage)) # store the sociomatrix rand.mat <- rand.net[,] # Update the network update(flomarriage, rand.mat, matrix.type="adjacency") # Try this with an edgelist rand.mat <- as.matrix.network.edgelist(flomarriage)[1:5,] update(flomarriage, rand.mat, matrix.type="edgelist")