ergm.sign (version 0.1.2)

mple_sign: Fit an ERGM with MPLE using a logistic regression model

Description

Returns a fitted logistic regression model used to calculate the maximum pseudolikelihood estimate (MPLE) of an exponential random graph model (ERGM).

Usage

mple_sign(
  formula,
  control = control.ergm(),
  seed = NULL,
  eval_lik = FALSE,
  ...
)

Value

An object of class ergm.

Arguments

formula

An ERGM formula with the network on the left-hand side.

control

A list of control parameters for ergmMPLE. By default, the covariance method is set to "Godambe".

seed

Optional integer to set the random seed for reproducibility when simulating networks for Godambe covariance estimation.

eval_lik

Logical indicating whether to evaluate the likelihood using path sampling.

...

Additional arguments passed to ergmMPLE.

Details

The MPLE is calculated by first computing matrices of positive and negative change statistics. These are then used to estimate the MPLE via logistic regression. Optionally, the covariance can be estimated using the Godambe method.

See Also

ergmMPLE, ergm, glm

Examples

data(tribes)
mple_sign(tribes ~ Pos(~edges) + Neg(~edges))