gof.vblpcm: Goodness of fit based on simulations from the fitted object.

Description

Create a goodness of fit statistics and plots based on the degree distributions of networks simulated fitted from a fitted variational approximation.

Usage

# S3 method for vblpcm
gof(object, ...,
         nsim=100,
         GOF=NULL,
         verbose=FALSE)

Arguments

object: fitted VBLPCM object; usually output from vblpcmfit() or vblpcmstart()
...: optional arguments for lower level functions
nsim: number of networks to simulate
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. Examples are the degree distribution ("degree"), minimum geodesic distances ("dist"), and shared partner distributions ("espartners" and "dspartners"). For the details on the possible <model terms>, see ergm-terms.
verbose: Provide verbose information on the progress of the simulation.

Author

Michael Salter-Townshend

Details

A sample of graphs is randomly drawn from the posterior of the vblpcmfit() result.

A plot of the summary measures may then be plotted using plot().

Examples

Run this code

data(sampson,package="VBLPCM")
v.start<-vblpcmstart(samplike,G=3,model="rreceiver",LSTEPS=1e3)
v.fit<-vblpcmfit(v.start,STEPS=20)
### plot the mean posterior positions
plot(v.fit, R2=0.05,main="Sampson's Monks: VB with Receiver Effects")
### Look at gof plots
plot(gof(v.fit,GOF=~distance,nsim=50))