ergmm-families {latentnet} | R Documentation |
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 (same for every dyad) whose success the response counts represent- normal
a mandatory
prior.var
andprior.var.df
parameter for the prior scale and degrees of freedom of the variance of the dyad values