Applied Network Science

Table 4 Results of both BERGM and BALERGM using formula y \(\sim\) edges + nodematch(“Grade”)

From: Hierarchical Bayesian adaptive lasso methods on exponential random graph models

Results
		Mean AR	Mean ESS	Mean squared error	Median squared error
BERGM	\(\theta _{1}\)	0.5286	222.16	4.641585	2.845891
BERGM	\(\theta _{2}\)	0.5286	220.69	4.641585	2.845891
BALERGM	\(\theta _{1}\)	0.5607	246.72	0.1960137	0.06896186
BALERGM	\(\theta _{2}\)	0.5607	221.82	0.1960137	0.06896186

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