R: Edge Weight Distribution Families

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` and `prior.var.df` parameter for the prior scale and degrees of freedom of the variance of the dyad values

[Package latentnet version 2.10.5 Index]