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statnet
Classes for Relational Data
PLEASE also add a NODELIST (ego, alter1, alter2). Empirical survey data mostly comes as a NODELIST. I have spent so much time with getting nodelists into statnet:  _Originally posted...
When called with a two-mode adjacency matrix, `as.network.matrix` will correctly interpret this as a graph with an enforced bipartition, with the passed matrix being the off-diagonal portion of the full...
The current implementation of modifiers for network objects attempts to modify it in place, emulating behaviour of C++, Java, and Python classes, and `R6` classes in R. This is accomplished...
It seems this is initialized to `numeric` by `network.initialize`, e.g. ``` require(network) nw
e.g. ``` require(network) nw as.matrix.network.edgelist(nw, as.sna.edgelist = TRUE) [,1] [,2] [,3] [1,] 1 2 1 [2,] 2 1 1 attr(,"n") [1] 2 attr(,"vnames") [1] 1 2 > as.edgelist(nw, as.sna.edgelist =...
Vlado's pajek site has been moved or otherwise is/was offline, which has produced errors for us on CRAN, because the documentation for `read.paj` and associated tests makes use of remote...
(This is related to, but not exactly the same as, the issue with two-mode adjacency processing with `as.matrix.data.frame`.) When passed a matrix as input, `network` and `as.network` will use `as.network.matrix`...
From a different thread: > Yeah, the matrix type heuristics have to make some judgment calls, and those are tricky in some cases. Currently, a square matrix is always assumed...
Many of them are severely out of date, and it's not clear what purpose they serve at this point. We could replace them with the "standard" Statnet copyright headers.