Bayesian Model Selection for Exponential Random Graph Models via Adjusted Pseudolikelihoods
Author:
Affiliation:
1. School of Mathematics and Statistics & Insight Centre for Data Analytics, University College Dublin, Dublin, Ireland
Funder
Science Foundation Ireland
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/10618600.2018.1448832
Reference51 articles.
1. A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood
2. Statistical Analysis of Non-Lattice Data
3. Efficiency of pseudolikelihood estimation for simple Gaussian fields
4. Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution
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