Markov random geometric graph, MRGG: A growth model for temporal dynamic networks-Reference-Cited by-同舟云学术

Markov random geometric graph, MRGG: A growth model for temporal dynamic networks

Published:2022-01-01 Issue:1 Volume:16 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Duchemin Quentin¹,De Castro Yohann¹

Affiliation:

1. LAMA, Univ Gustave Eiffel, Univ Paris Est Créteil, CNRS F-77447 Marne-la-Vallée, France Institut Camille Jordan, École Centrale de Lyon, Lyon, France

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability,Statistics, Probability and Uncertainty

Reference34 articles.

1. Roberts, G. O. and Rosenthal, J. S. (2004). General state space Markov chains and MCMC algorithms. Probability Surveys 1 20–71.

2. Arlot, S. (2019). Minimal penalties and the slope heuristics: a survey. Journal de la société française de statistique 160 1–106.

3. Araya, E. and De Castro, Y. (2019). Latent Distance Estimation for Random Geometric Graphs. In Advances in Neural Information Processing Systems 8721–8731.

4. Backstrom, L., Huttenlocher, D., Kleinberg, J. and Lan, X. (2006). Group formation in large social networks: membership, growth, and evolution. In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining 44–54.

5. Bandeira, A. S. and van Handel, R. (2016). Sharp nonasymptotic bounds on the norm of random matrices with independent entries. Ann. Probab. 44 2479–2506.

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