R: A simple implementation of bridge sampling to evaluate...

ergm.bridge.llr {ergm} | R Documentation

## 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:

`llr` | The estimated log-ratio.
`llrs` | The estimated log-ratios for each of the `nsteps` bridges.
`path` | A numeric matrix with nsteps rows, with each row being the respective bridge's parameter configuration.
`stats` | A numeric matrix with nsteps rows, with each row being the respective bridge's vector of simulated statistics.
`Dtheta.Du` | The gradient vector of the parameter values with respect to position of the bridge.

### 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`

[Package ergm version 3.8.0 Index]