ergm (version 3.6.1)

ergm.bridge.llr: A simple implementation of bridge sampling to evaluate log-likelihood-ratio between two ERGM configurations

Description

ergm.bridge.llr uses bridge sampling with geometric spacing to estimate the difference between the log-likelihoods of two parameter vectors for an ERGM via repeated calls to simulate.formula.ergm.

ergm.bridge.0.llk is a convenience wrapper around ergm.bridge.llr: returns the log-likelihood of configuration `theta' relative to the reference measure. That is, the configuration with theta=0 is defined as having log-likelihood of 0

See also ergm.bridge.dindstart.llk to use dyad-independent ERGM as a staring point.

Usage

ergm.bridge.llr(object,  response=NULL,  constraints=~.,  from,  to,  basis=NULL,  verbose=FALSE,  ...,  llronly=FALSE,  control=control.ergm.bridge())  ergm.bridge.0.llk(object,  response=response,  coef,  ...,  llkonly=TRUE,  control=control.ergm.bridge())

Arguments

object

A model formula. See ergm for details.

response

Not for release.

constraints

A one-sided formula specifying one or more constraints on the support of the distribution of the networks being simulated. See the documentation for a similar argument for ergm for more information. For simulate.formula, defaults to no constraints. For simulate.ergm, defaults to using the same constraints as those with which object was fitted.

from, to

The initial and final parameter vectors.

basis

An optional network object to start the Markov chain. If omitted, the default is the left-hand-side of the object.

verbose

Logical: If TRUE, print detailed information.

...

Further arguments to ergm.bridge.llr and simulate.formula.ergm.

llronly

Logical: If TRUE, only the estiamted log-ratio will be returned.

control

Control arguments. See control.ergm.bridge for details.

coef

A vector of coefficients for the configuration of interest.

llkonly

Whether only the estiamted log-likelihood should be returned. (Defaults to TRUE.)

Value

If llronly=TRUE, returns the scalar log-likelihood-ratio. Otherwise, returns a list with the following components:

References

Hunter, D. R. and Handcock, M. S. (2006) Inference in curved exponential family models for networks, Journal of Computational and Graphical Statistics.

See Also

simulate.formula.ergm, ergm.bridge.dindstart.llk