R: Conduct Goodness-of-Fit Diagnostics on a Exponential Family...

gof {ergm} | R Documentation

## Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model

### Description

`gof` calculates p-values for geodesic distance, degree, and reachability summaries to diagnose the goodness-of-fit of exponential family random graph models. See `ergm` for more information on these models.

### Usage

    ## Default S3 method:
    gof(object,...)
    ## S3 method for class 'formula'
    gof(object,
                          ...,
                          coef=NULL,
                          GOF=NULL,
                          constraints=~.,
                          control=control.gof.formula(),
    		      unconditional=TRUE,
                          verbose=FALSE)
    ## S3 method for class 'ergm'
    gof(object,
                       ...,
                       coef=NULL,
                       GOF=NULL,
                       constraints=NULL,
                       control=control.gof.ergm(),
                       verbose=FALSE)

### Arguments

`object` | an R object. Either a formula or an `ergm` object. See documentation for `ergm`.
`...` | Additional arguments, to be passed to lower-level functions in the future.
`coef` | When given either a formula or an object of class ergm, `coef` are the parameters from which the sample is drawn. By default set to a vector of 0.
`GOF` | formula; an R formula object, of the form `~ <model terms>` specifying the statistics to use to diagnosis the goodness-of-fit of the model. They do not need to be in the model formula specified in `formula`, and typically are not. Currently supported terms are the degree distribution (“degree” for undirected graphs, or “idegree” and/or “odegree” for directed graphs), geodesic distances (“distance”), shared partner distributions (“espartners” and “dspartners”), the triad census (“triadcensus”), and the terms of the original model (“model”). The default formula for undirected networks is `~ degree + espartners + distance + model`, and the default formula for directed networks is `~ idegree + odegree + espartners + distance + model`. By default a “model” term is added to the formula. It is a very useful overall validity check and a reminder of the statistical variation in the estimates of the mean value parameters. To omit the “model” term, add “- model” to the formula.
`constraints` | A one-sided formula specifying one or more constraints on the support of the distribution of the networks being modeled. See the help for similarly-named argument in `ergm` for more information. For `gof.formula`, defaults to unconstrained. For `gof.ergm`, defaults to the constraints with which `object` was fitted.
`control` | A list to control parameters, constructed using `control.gof.formula` or `control.gof.ergm` (which have different defaults).
`unconditional` | logical; if `TRUE`, the simulation is unconditional on the observed dyads. if not `TRUE`, the simulation is conditional on the observed dyads. This is primarily used internally when the network has missing data and a conditional GoF is produced.
`verbose` | Provide verbose information on the progress of the simulation.

### Details

A sample of graphs is randomly drawn from the specified model. The first argument is typically the output of a call to `ergm` and the model used for that call is the one fit.

A plot of the summary measures is plotted. More information can be found by looking at the documentation of `ergm`.

For `GOF = ~model`, the model's observed sufficient statistics are plotted as quantiles of the simulated sample. In a good fit, the observed statistics should be near the sample median (0.5).

For `gof.ergm` and `gof.formula`, default behavior depends on the directedness of the network involved; if undirected then degree, espartners, and distance are used as default properties to examine. If the network in question is directed, “degree” in the above is replaced by idegree and odegree.

### Value

`gof`, `gof.ergm`, and `gof.formula` return an object of class `gofobject`. This is a list of the tables of statistics and p-values. This is typically plotted using `plot.gofobject`.

### See Also

ergm, network, simulate.ergm, summary.ergm, plot.gofobject

### Examples

    data(florentine)
    gest <- ergm(flomarriage ~ edges + kstar(2))
    gest
    summary(gest)

    # test the gof.ergm function
    gofflo <- gof(gest)
    gofflo
    summary(gofflo)

    # Plot all three on the same page
    # with nice margins
    par(mfrow=c(1,3))
    par(oma=c(0.5,2,1,0.5))
    plot(gofflo)

    # And now the log-odds
    plot(gofflo, plotlogodds=TRUE)

    # Use the formula version of gof
    gofflo2 <-gof(flomarriage ~ edges + kstar(2), coef=c(-1.6339, 0.0049))
    plot(gofflo2)

[Package ergm version 3.8.0 Index]