gof.ergm.ego {ergm.ego} | R Documentation |
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 |
... |
Additional arguments. Unused by |
GOF |
A string specifying the statistics whose goodness of fit is to be
evaluated. Currently, only “degree”, “espartners” and “model” are
implemented; see |
control |
A list to control parameters, constructed using
|
verbose |
Provide verbose information on the progress of the simulation. |
x |
an object returned by |
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. 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)