The reputation of the maximum pseudolikelihood estimator (MPLE) for Exponential Random Graph Models (ERGM) has undergone a drastic change over past 30 years. While first receiving broad support, mainly due to its computational feasibility and lack alternatives, general opinions started with introduction approximate likelihood (MLE) methods that became practicable increasing computing power MCMC...

Exponential family random graph models (ERGMs) are widely used to model networks by parameterizing probability in terms of a set user-selected sufficient statistics. Equivalently, ERGMs ca...

This paper introduces a general family of continuous distributions, based on the exponential-logarithmic distribution and odd transformation. It is called “odd exponential logarithmic family”. We intend to create novel distributions with desired qualities for practical applications, using unique properties as an initial inspiration. Thus, we present some special members this that stand out vers...