Model-based clustering of time-evolving networks through temporal exponential-family random graph models

Mathematics

• Discrete Time 100%
• Graph Model 100%
• Exponential Family 100%
• Model-Based Clustering 100%
• Approximates 50%
• Simulation Study 50%
• Model Selection Criterion 50%
• Statistical Technique 50%
• Network Model 50%
• Conditional Likelihood 50%
• Maximum Likelihood Estimate 50%

Computer Science

• discrete-time 100%
• Random Graphs 100%
• Dynamic Network 50%
• Research Question 50%
• Network Parameter 50%
• Selection Criterion 50%
• Statistical Technique 50%
• Simulation Study 50%
• maximum-likelihood 50%
• Group Structure 50%
• Likelihood Estimate 50%
• Conditional Likelihood 50%

Keyphrases

• Exponential Random Graph Models 100%
• Model-based Clustering 100%
• Simulation Study 25%
• Mixing Ratio 25%
• Network Model 25%
• Effective Model 25%
• Collaborative Networks 25%
• Discrete-time 25%
• Expectation-maximization Algorithm 25%
• Network Parameters 25%
• Model Selection Criteria 25%
• Statistical Techniques 25%
• Network Applications 25%
• Group-based 25%
• Dynamic Networks 25%
• Connectivity Pattern 25%
• Group Structure 25%
• Number of Groups 25%
• Variational 25%
• Clustering Framework 25%
• Conditional Likelihood 25%