ergm.estfun | R Documentation |
The estimating function for an ERGM is the score function: the gradient of the log-likelihood, equalling η'(θ)^\top \{g(y)-μ(θ)\}, where g(y) is a p-vector of observed network sufficient statistic, μ(θ) is the expected value of the sufficient statistic under the model for parameter value θ, and η'(θ) is the p by q Jacobian matrix of the mapping from curved parameters to natural parmeters. If the model is linear, all non-offset statistics are passed. If the model is curved, the score estimating equations (3.1) by Hunter and Handcock (2006) are given instead.
ergm.estfun(stats, theta, model, ...) ## S3 method for class 'numeric' ergm.estfun(stats, theta, model, ...) ## S3 method for class 'matrix' ergm.estfun(stats, theta, model, ...) ## S3 method for class 'mcmc' ergm.estfun(stats, theta, model, ...) ## S3 method for class 'mcmc.list' ergm.estfun(stats, theta, model, ...)
stats |
An object representing sample statistics with observed values subtracted out. |
theta |
Model parameter q-vector. |
model |
An |
... |
Additional arguments for methods. |
An object of the same class as stats
containing
q-vectors of estimating function values.
numeric
: Method for numeric vectors of length p.
matrix
: Method for matrices with p columns.
mcmc
: Method for mcmc
objects with p variables.
mcmc.list
: Method for mcmc.list
objects with p variables.
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