ergmm-families: Edge Weight Distribution Families

In statnet/latentnet: Latent Position and Cluster Models for Statistical Networks

Edge Weight Distribution Families

Description

Family-link combinations supported by ergmm().

Details

Each supported family has a family of functions, of the form pY.-, lpY.-, EY.-, dlpY.deta.-, dlpY.ddispersion.-, lpYc.-, rsm.-, followed by the family's name, for the respective family's name, representing the family's likelihood, log-likelihood, expectation, derivative of log-likelihood with repect to the linear predictor, derivative of log-likelihood with respect to the dispersion parameter, log-normalizing-constant, and random sociomatrix generation functions.

On the C side, similar functions exist, but becuase of static typing, are also provided for “continuous” versions of those families. These should not be used on their own, but are used in estimating MKL positions from the posterior distribution.

Family-link combinations

ID	C name	R name	Type	Family	Link
1	Bernoulli_logit	Bernoulli.logit	Discrete	Bernoulli	logit
2	binomial_logit	binomial.logit	Discrete	binomial	logit
3	Poisson_log	Poisson.log	Discrete	Possion	log
4	Bernoulli_cont_logit	NA	Continuous	Bernoulli	logit
5	binomial_cont_logit	NA	Continuous	binomial	logit
6	Poisson_cont_log	NA	Continuous	Possion	log
7	normal_identity	normal.identity	Continuous	normal	identity

.link can be omited when not ambiguous. Some families require an appropriate fam.par argument to be supplied to ergmm():

binomial families

A mandatory trials parameter for the number of trials whose success the response counts represent. This can be a single number if the same for all dyads, or a matrix if not. For non-bipartite networks, the matrix must be a square matrix with dimension equal to the number of nodes; for a bipartite network, it can also be a rectangular incidence matrix. If the network is undirected, the lower triangle is used.

normal

Mandatory prior.var and prior.var.df parameters for the prior scale and degrees of freedom of the variance of the dyad values.

statnet/latentnet documentation built on April 13, 2025, 1:11 a.m.