IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v96y2001mseptemberp1077-1087.html
   My bibliography  Save this article

Estimation and Prediction for Stochastic Blockstructures

Author

Listed:
  • Nowicki K.
  • Snijders T. A. B.

Abstract

No abstract is available for this item.

Suggested Citation

  • Nowicki K. & Snijders T. A. B., 2001. "Estimation and Prediction for Stochastic Blockstructures," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1077-1087, September.
    • Handle: RePEc:bes:jnlasa:v:96:y:2001:m:september:p:1077-1087
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/asa/jasa/2001/00000096/00000455/art00025
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hledik, Juraj & Rastelli, Riccardo, 2020. "A dynamic network model to measure exposure diversification in the Austrian interbank market," ESRB Working Paper Series 109, European Systemic Risk Board.
    2. Yunpeng Zhao & Qing Pan & Chengan Du, 2019. "Logistic regression augmented community detection for network data with application in identifying autism‐related gene pathways," Biometrics, The International Biometric Society, vol. 75(1), pages 222-234, March.
    3. Xu, Xiu & Wang, Weining & Shin, Yongcheol, 2020. "Dynamic Spatial Network Quantile Autoregression," IRTG 1792 Discussion Papers 2020-024, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    4. Teague R. Henry & Kathleen M. Gates & Mitchell J. Prinstein & Douglas Steinley, 2020. "Modeling Heterogeneous Peer Assortment Effects Using Finite Mixture Exponential Random Graph Models," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 8-34, March.
    5. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    6. Li Guo & Wolfgang Karl Härdle & Yubo Tao, 2024. "A Time-Varying Network for Cryptocurrencies," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 437-456, April.
    7. Arora, Saurabh & Sanditov, Bulat, 2009. "Caste as Community? Networks of social affinity in a South Indian village," MERIT Working Papers 2009-037, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    8. Saint‐Clair Chabert‐Liddell & Pierre Barbillon & Sophie Donnet, 2022. "Impact of the mesoscale structure of a bipartite ecological interaction network on its robustness through a probabilistic modeling," Environmetrics, John Wiley & Sons, Ltd., vol. 33(2), March.
    9. Sirio Legramanti & Tommaso Rigon & Daniele Durante, 2022. "Bayesian Testing for Exogenous Partition Structures in Stochastic Block Models," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 108-126, June.
    10. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    11. Falk Bräuning & Siem Jan Koopman, 2016. "The Dynamic Factor Network Model with an Application to Global Credit-Risk," Tinbergen Institute Discussion Papers 16-105/III, Tinbergen Institute.
    12. ter Braak, Cajo J.F. & Kourmpetis, Yiannis & Kiers, Henk A.L. & Bink, Marco C.A.M., 2009. "Approximating a similarity matrix by a latent class model: A reappraisal of additive fuzzy clustering," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 3183-3193, June.
    13. Xiu Xu & Weining Wang & Yongcheol Shin & Chaowen Zheng, 2024. "Dynamic Network Quantile Regression Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 407-421, April.
    14. Michael Brusco & Douglas Steinley, 2011. "A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 612-633, October.
    15. Tracy M. Sweet, 2015. "Incorporating Covariates Into Stochastic Blockmodels," Journal of Educational and Behavioral Statistics, , vol. 40(6), pages 635-664, December.
    16. Prasenjit Ghosh & Debdeep Pati & Anirban Bhattacharya, 2020. "Posterior Contraction Rates for Stochastic Block Models," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 448-476, August.
    17. Yan, Donghui & Chen, Aiyou & Jordan, Michael I., 2013. "Cluster Forests," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 178-192.
    18. Irene Crimaldi & Michela Del Vicario & Greg Morrison & Walter Quattrociocchi & Massimo Riccaboni, 2015. "Homophily and Triadic Closure in Evolving Social Networks," Working Papers 3/2015, IMT School for Advanced Studies Lucca, revised May 2015.
    19. Tom Britton, 2020. "Epidemic models on social networks—With inference," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 222-241, August.
    20. Michael Schweinberger, 2020. "Statistical inference for continuous‐time Markov processes with block structure based on discrete‐time network data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 342-362, August.
    21. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
    22. Bartolucci, Francesco & Marino, Maria Francesca & Pandolfi, Silvia, 2015. "Composite likelihood inference for hidden Markov models for dynamic networks," MPRA Paper 67242, University Library of Munich, Germany.
    23. Juraj Hledik & Riccardo Rastelli, 2018. "A dynamic network model to measure exposure diversification in the Austrian interbank market," Papers 1804.01367, arXiv.org, revised Aug 2018.
    24. Dragana M. Pavlović & Bryan R.L. Guillaume & Soroosh Afyouni & Thomas E. Nichols, 2020. "Multi‐subject stochastic blockmodels with mixed effects for adaptive analysis of individual differences in human brain network cluster structure," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 363-396, August.
    25. Brayden G King & Elisabeth S. Clemens & Melissa Fry, 2011. "Identity Realization and Organizational Forms: Differentiation and Consolidation of Identities Among Arizona's Charter Schools," Organization Science, INFORMS, vol. 22(3), pages 554-572, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bes:jnlasa:v:96:y:2001:m:september:p:1077-1087. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.