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ergm-references

Reference Measures for Exponential-Family Random Graph Models


Description

This page describes the possible reference measures (baseline distributions) for found in the ergm package, particularly the default (Bernoulli) reference measure for binary ERGMs.

The reference measure is specified on the RHS of a one-sided formula passed as the reference argument to ergm. See the ergm documentation for a complete description of how reference measures are specified.

Possible reference measures to represent baseline distributions

Reference measures currently available are:

Bernoulli

Bernoulli-reference ERGM: Specifies each dyad's baseline distribution to be Bernoulli with probability of the tie being 0.5. This is the only reference measure used in binary mode.

DiscUnif(a,b)

Discrete-Uniform-reference ERGM: Specifies each dyad's baseline distribution to be discrete uniform between a and b (both inclusive): h(y)=1, with the support being a,a+1,...,b-1,b. At this time, both a and b must be finite.

Unif(a,b)

Coninuous-Uniform-reference ERGM: Specifies each dyad's baseline distribution to be continuous uniform between a and b (both inclusive): h(y)=1, with the support being [a,b]. At this time, both a and b must be finite.

StdNormal

Standard-Normal-reference ERGM: Specifies each dyad's baseline distribution to be the normal distribution with mean 0 and variance 1.

References

Hunter DR, Handcock MS, Butts CT, Goodreau SM, Morris M (2008b). ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks. Journal of Statistical Software, 24(3). https://www.jstatsoft.org/v24/i03/.

Krivitsky PN (2012). Exponential-Family Random Graph Models for Valued Networks. Electronic Journal of Statistics, 2012, 6, 1100-1128. doi: 10.1214/12-EJS696

See Also

ergm, network, %v%, %n%, sna, summary.ergm, print.ergm


ergm

Fit, Simulate and Diagnose Exponential-Family Models for Networks

v3.11.0
GPL-3 + file LICENSE
Authors
Mark S. Handcock [aut], David R. Hunter [aut], Carter T. Butts [aut], Steven M. Goodreau [aut], Pavel N. Krivitsky [aut, cre] (<https://orcid.org/0000-0002-9101-3362>), Martina Morris [aut], Li Wang [ctb], Kirk Li [ctb], Skye Bender-deMoll [ctb], Chad Klumb [ctb], Michał Bojanowski [ctb], Ben Bolker [ctb]
Initial release
2020-10-14

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