How do individuals' network selection decisions create unique network structures? Despite
broad sociological interest in the micro-level social interactions that create macro-level …

The collection of data on populations of networks is becoming increasingly common, where
each data point can be seen as a realisation of a network-valued random variable …

Claiming causal inferences in network settings necessitates careful consideration of the
often complex dependency between outcomes for actors. Of particular importance are …

The first purpose of this study is to define the network parameters that enable systemic
analysis of international relations, identifying trends towards isolationism and expansionism …

Bayesian Analysis of Exponential Random Graph Models Using Stochastic Gradient Markov
Chain Monte Carlo Page 1 Bayesian Analysis (2024) 19, Number 2, pp. 595–621 Bayesian …

Social actors are often embedded in multiple social networks, and there is a growing interest
in studying social systems from a multiplex network perspective. In this paper, we propose a …

The analysis of network data has become an increasingly prominent and demanding field
across multiple research fields including data science, health, and social sciences, requiring …

The stochastic actor oriented model (SAOM) is a method for modelling social interactions
and social behaviour over time. It can be used to model drivers of dynamic interactions using …

Rankings are a type of preference elicitation that arise in experiments where assessors
arrange items, for example, in decreasing order of utility. Orderings of n items labelled {1 …

Given a smooth function $ f $, we develop a general approach to turn Monte Carlo samples
with expectation $ m $ into an unbiased estimate of $ f (m) $. Specifically, we develop …