gof.vblpcm {VBLPCM} | R Documentation |
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 class '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
|
verbose |
Provide verbose information on the progress of the simulation. |
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().
Author(s)
Michael Salter-Townshend
See Also
latentnet::gof.ergmm
Examples
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))