bgof {Bergm}  R Documentation 
Function to calculate summaries for degree, minimum geodesic distances, and edgewise shared partner distributions to diagnose the Bayesian goodnessoffit of exponential random graph models.
bgof(
x,
sample.size = 100,
aux.iters = 10000,
n.deg = NULL,
n.dist = NULL,
n.esp = NULL,
n.ideg = NULL,
n.odeg = NULL,
...
)
x 
an 
sample.size 
count; number of networks to be simulated and compared to the observed network. 
aux.iters 
count; number of iterations used for network simulation. 
n.deg 
count; used to plot only the first

n.dist 
count; used to plot only the first

n.esp 
count; used to plot only the first

n.ideg 
count; used to plot only the first

n.odeg 
count; used to plot only the first

... 
additional arguments, to be passed to lowerlevel functions. 
Caimo, A. and Friel, N. (2011), "Bayesian Inference for Exponential Random Graph Models," Social Networks, 33(1), 4155. https://arxiv.org/abs/1007.5192
Caimo, A. and Friel, N. (2014), "Bergm: Bayesian Exponential Random Graphs in R," Journal of Statistical Software, 61(2), 125. https://www.jstatsoft.org/v61/i02
## Not run:
# Load the florentine marriage network
data(florentine)
# Posterior parameter estimation:
p.flo < bergm(flomarriage ~ edges + kstar(2),
burn.in = 50,
aux.iters = 500,
main.iters = 1000,
gamma = 1.2)
# Bayesian goodnessoffit test:
bgof(p.flo,
aux.iters = 500,
sample.size = 30,
n.deg = 10,
n.dist = 9,
n.esp = 6)
## End(Not run)