Consistent structure estimation of exponential-family random graph models with block structure
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Publication:2295031
DOI10.3150/19-BEJ1153zbMath1466.62348arXiv1702.07801WikidataQ115488545 ScholiaQ115488545MaRDI QIDQ2295031
Publication date: 12 February 2020
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1702.07801
Asymptotic properties of parametric estimators (62F12) Random graphs (graph-theoretic aspects) (05C80) Probabilistic graphical models (62H22)
Related Items (5)
Large-scale estimation of random graph models with local dependence ⋮ Discussion to: \textit{Bayesian graphical models for modern biological applications} by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo ⋮ Statistical inference for continuous‐time Markov processes with block structure based on discrete‐time network data ⋮ Exponential-family models of random graphs: inference in finite, super and infinite population scenarios ⋮ Consistent structure estimation of exponential-family random graph models with block structure
Cites Work
- Unnamed Item
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- Pseudo-likelihood methods for community detection in large sparse networks
- Exponential-family random graph models for valued networks
- Fast community detection by SCORE
- Rate-optimal graphon estimation
- On the question of effective sample size in network modeling: an asymptotic inquiry
- Minimax rates of community detection in stochastic block models
- Consistency under sampling of exponential random graph models
- Maximum likelihood estimation in the \(\beta\)-model
- Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters
- Reconstruction and estimation in the planted partition model
- Random graphs with a given degree sequence
- Spectral clustering and the high-dimensional stochastic blockmodel
- Mixing time of exponential random graphs
- The method of moments and degree distributions for network models
- Logit models and logistic regressions for social networks. I: An introduction to Markov graphs and \(p^*\)
- Large-scale estimation of random graph models with local dependence
- Consistency of community detection in networks under degree-corrected stochastic block models
- Consistency of maximum-likelihood and variational estimators in the stochastic block model
- On the geometry of discrete exponential families with application to exponential random graph models
- A statistical framework for modern network science
- Concentration and consistency results for canonical and curved exponential-family models of random graphs
- Exponential-family models of random graphs: inference in finite, super and infinite population scenarios
- Consistent structure estimation of exponential-family random graph models with block structure
- Consistency of spectral clustering in stochastic block models
- Estimating and understanding exponential random graph models
- Concentration inequalities for dependent random variables via the martingale method
- Stochastic blockmodels with a growing number of classes
- Introduction to Random Graphs
- A nonparametric view of network models and Newman–Girvan and other modularities
- Conditional Marginalization for Exponential Random Graph Models
- Mixed membership stochastic blockmodels
- Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters
- The highest dimensional stochastic blockmodel with a regularized estimator
- Instability, Sensitivity, and Degeneracy of Discrete Exponential Families
- Asymptotics in undirected random graph models parameterized by the strengths of vertices
- Goodness of Fit of Social Network Models
- Markov Graphs
- An Exponential Family of Probability Distributions for Directed Graphs
- Estimation and Prediction for Stochastic Blockstructures
- Dealing With Label Switching in Mixture Models
- The random triangle model
- Random Networks, Graphical Models and Exchangeability
- Local Dependence in Random Graph Models: Characterization, Properties and Statistical Inference
- Covariate-assisted spectral clustering
- Random Graphs
- Consistency and Asymptotic Normality of MLE's for Exponential Models
- Graph colouring and the probabilistic method
- Asymptotics in directed exponential random graph models with an increasing bi-degree sequence
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