ergm: ergm.estfun – R documentation

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ergm.estfun

Compute the Sample Estimating Function Values of an ERGM.

Description

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.

Usage

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, ...)

Arguments

`stats`	An object representing sample statistics with observed values subtracted out.
`theta`	Model parameter q-vector.
`model`	An `ergm_model` object or its `etamap` element.
`...`	Additional arguments for methods.

Value

An object of the same class as stats containing q-vectors of estimating function values.

Methods (by class)

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.

ergm

Fit, Simulate and Diagnose Exponential-Family Models for Networks

v3.11.0

GPL-3 + file LICENSE

Authors

Mark S. Handcock [aut], David R. Hunter [aut], Carter T. Butts [aut], Steven M. Goodreau [aut], Pavel N. Krivitsky [aut, cre] (<https://orcid.org/0000-0002-9101-3362>), Martina Morris [aut], Li Wang [ctb], Kirk Li [ctb], Skye Bender-deMoll [ctb], Chad Klumb [ctb], Michał Bojanowski [ctb], Ben Bolker [ctb]

Initial release

2020-10-14