gof.ergm.ego: Conduct Goodness-of-Fit Diagnostics on a Exponential Family...

In ergm.ego: Fit, Simulate and Diagnose Exponential-Family Random Graph Models to Egocentrically Sampled Network Data

Conduct Goodness-of-Fit Diagnostics on a Exponential Family Random Graph Model fit to Egocentrically Sampled Data

Description

gof.ergm.ego implements the gof method for ergm.ego fit objects.

An enhanced plotting method is also provided, giving uncertainty bars for the observed statistics as well.

Usage

## S3 method for class 'ergm.ego'
gof(
  object,
  ...,
  GOF = c("model", "degree", "espartners"),
  control = control.gof.ergm(),
  verbose = FALSE
)

## S3 method for class 'gof.ergm.ego'
plot(x, ..., ego.conf.level = 0.95)

Arguments

object	An ergm.ego fit.
...	Additional arguments. Unused by gof.ergm.ego(), passed to ergm::plot.gof() by plot.gof.ergm.ego()
GOF	A string specifying the statistics whose goodness of fit is to be evaluated. Currently, only “degree”, “espartners” and “model” are implemented; see gof documentation for details.
control	A list to control parameters, constructed using control.gof.formula or control.gof.ergm (which have different defaults).
verbose	Provide verbose information on the progress of the simulation.
x	an object returned by gof.ergm.ego().
ego.conf.level	confidence level for the observed statistic estimates as well.

Value

An object of class gof.ergm.ego, inheriting from gof.ergm.

Author(s)

Pavel N. Krivitsky

References

• David R. Hunter, Steven M. Goodreau, and Mark S. Handcock (2008). "Goodness of Fit of Social Network Models." Journal of the American Statistical Association, 103:481: 248–258. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1198/016214507000000446")}

See Also

For examples, see ergm.ego.

Examples

data(faux.mesa.high)
fmh.ego <- as.egor(faux.mesa.high)

head(fmh.ego)

egofit <- ergm.ego(fmh.ego~edges+degree(0:3)+nodefactor("Race")+nodematch("Race")
                         +nodefactor("Sex")+nodematch("Sex")+absdiff("Grade"), 
                          popsize=network.size(faux.mesa.high))

# Check whether the model "converged":
(modelgof <- gof(egofit, GOF="model"))
plot(modelgof)

# Check whether the model reconstructs the degree distribution:
(deggof <- gof(egofit, GOF="degree"))
plot(deggof)

ergm.ego documentation built on May 31, 2023, 7:28 p.m.