[statnet_help] Examples of dynamic population equilibria with more than two groups in EpiModel stochastic network models

b bzusman at gmail.com
Fri Oct 30 23:09:44 PDT 2020


I am trying to incorporate custom arrival and departure modules into a
network model (SEIRQ) with 4 different "types" of individuals (still in
v1.8). The context interprets "arrivals" and "departures" as replacements
for each other from a fixed reservoir, without actual deletion of these
nodes as in the mortality module. The total N is fixed. When one "departs",
they can no longer form partnerships, and an arrival of the same type
replaces that individual, until a few time steps later, when the exchange
happens again. How many time steps later is determined by the type, and
each of the 4 types has unique durations to remain in and out of the
network (mimicking their work schedule, independent of status). I am having
difficulty coding this population to maintain a dynamic equilibrium. It
would be easier in a .icm with 2 groups or types that each arrived for X
days, then departed for X days, with all the rates balancing.

Surprisingly, I haven't been able to find any examples in the literature of
EpiModel network models using (non-birth/death) arrival and departure
modules with a fixed population. If you can point me in the direction of an
example, it would be very instructive to see how dynamic equilibrium is
coded into a network model with more than two groups when you can't simply
calibrate birth and death rates to equilibrium.

Thanks,
Benji Zusman
University of Florida


On Mon, Oct 12, 2020, 3:02 PM <
statnet_help-request at mailman13.u.washington.edu> wrote:


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> 1. How does ERGMs deal with parameters that cannot be estimated

> from the data? (David Kretschmer)

>

>

>

> ---------- Forwarded message ----------

> From: David Kretschmer <dkretsch at mail.uni-mannheim.de>

> To: statnet_help at u.washington.edu

> Cc:

> Bcc:

> Date: Mon, 12 Oct 2020 17:23:17 +0200

> Subject: [statnet_help] How does ERGMs deal with parameters that cannot be

> estimated from the data?

> Hello dear list users,

>

> I estimate an ERGM that includes a parameter that cannot be estimated from

> the data, i.e., it contains a dyadic covariate that has the value zero for

> each dyad.

>

> To my surprise, running an ERGM on this data does still provide a

> coefficient estimate for the parameter that cannot be estimated from the

> data. Under normal conditions, the coefficient estimate is zero, and the

> standard error and all other elements in the ERGM output are NA. Still, I

> wondered why a coefficient value of zero is reported even though the

> parameter clearly cannot be estimated from the data.

>

> Furthermore, when using the “constraints” argument of ERGM (constraints =

> ~bd(maxout = 5) in my case), the reported coefficient estimate is no longer

> zero but some other, seemingly random value that frequently is very high

> (e.g. 51 in one example run). Here, I also wonder how the ERGM arrives at

> this value.

>

> In general, it is clear to me that these coefficient estimates are without

> substantive meaning. However, I wonder why they are still reported in the

> ERGM output and how the corresponding values come about.

>

> Any help would be greatly appreciated.

>

> Best,

> David

>

>

>

> --

> David Kretschmer

> Universität Mannheim

> Mannheimer Zentrum für Europäische Sozialforschung (MZES)

> A5, 6

> 68159 Mannheim

> Tel.: +49-621-181-2024

>

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