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Event history analysis of dynamic communication networks

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Sit, By T., Ying, Z. and Yu, Yi (2021) Event history analysis of dynamic communication networks. Biometrika, 108 (1). pp. 223-230. doi:10.1093/biomet/asaa045 ISSN 0006-3444.

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Official URL: https://doi.org/10.1093/biomet/asaa045

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Abstract

Statistical analysis on networks has received growing attention due to demand from various emerging applications. In dynamic networks, one of the key interests is to model the event history of time-stamped interactions among nodes. We model dynamic directed networks via multivariate counting processes. A pseudo partial likelihood approach is exploited to capture the network dependence structure. Asymptotic results are established. Numerical experiments are performed to demonstrate the effectiveness of our proposal.

Item Type: Journal Article
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH): Event history analysis, Survival analysis (Biometry), Telecommunication systems, Multivariate analysis, Point processes -- Mathematical models, Mathematical statistics
Journal or Publication Title: Biometrika
Publisher: Biometrika Trust ; Oxford University Press
ISSN: 0006-3444
Official Date: March 2021
Dates:
DateEvent
March 2021Published
24 September 2020Available
26 February 2020Accepted
Volume: 108
Number: 1
Page Range: pp. 223-230
DOI: 10.1093/biomet/asaa045
Status: Peer Reviewed
Publication Status: Published
Reuse Statement (publisher, data, author rights): This is a pre-copyedited, author-produced version of an article accepted for publication in Biometrika following peer review. The version of record T Sit, Z Ying, Y Yu, Event history analysis of dynamic networks, Biometrika, , asaa045, is available online at: https://doi.org/10.1093/biomet/asaa045
Access rights to Published version: Restricted or Subscription Access
Date of first compliant deposit: 5 March 2020
Date of first compliant Open Access: 24 September 2021
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
14317716University Grants Committee (Hong Kong, China)http://viaf.org/viaf/136370456
14301618University Grants Committee (Hong Kong, China)http://viaf.org/viaf/136370456
IIS-1633360National Science Foundationhttp://dx.doi.org/10.13039/501100008982
R01GM047845National Institutes of Healthhttp://dx.doi.org/10.13039/100000002
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