[statnet_help] TERGM for weighted networks
david.fisher at abdn.ac.uk
Mon Jul 6 00:59:06 PDT 2020
Hi Vivek (and list),
Stochastic actor oriented models can handle 2 different strengths of ties (last time I checked) with a dynamic framework. Although not ERGMs, it still might be of interest.
Check out the RSiena scripts on this page, http://www.stats.ox.ac.uk/~snijders/siena/ I think script #11 fits a dynamic network model that is “ordered” (i.e. ties with different weights). You’ll probably need to look at the manual and the more simple scripts first though to make sense of it.
From: Vivek Kulkarni <viveksck at gmail.com>
Sent: 04 July 2020 16:17
To: Pavel Krivitsky <p.krivitsky at unsw.edu.au>
Cc: statnet_help at u.washington.edu
Subject: Re: [statnet_help] TERGM for weighted networks
Thanks for letting me know! In my setting, the weights are just counts that represent the number of observed co-occurrences between words in a co-occurrence network.
On Sat, Jul 4, 2020 at 2:45 AM Pavel Krivitsky <p.krivitsky at unsw.edu.au<mailto:p.krivitsky at unsw.edu.au>> wrote:
ERGM-based modelling of dynamic weighted network is an open problem,
which I am hoping to tackle in the next year or so. In the meantime,
can you tell me what the weights are in this case? Counts? Categories?
Ranks? Values between 0 and 1?
On Mon, 2020-06-29 at 10:34 -0700, Vivek Kulkarni wrote:
> I have several snapshots of a weighted network through time and I
> wanted to analyze the formation and decay of edges in this
> temporal network. I notice that TERGM can help me do that, but I was
> wondering if TERGm also supports weighted graphs/networks? I know the
> package "valued" supports weighted edges, but then it does not seem
> to support temporal networks. Thanks a ton!
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> statnet_help at u.washington.edu<mailto:statnet_help at u.washington.edu>
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