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dc.contributor.authorZhang, Li-Chun
dc.date.accessioned2023-03-02T13:09:42Z
dc.date.available2023-03-02T13:09:42Z
dc.date.created2023-01-13T07:56:59Z
dc.date.issued2021-12-10
dc.identifier.citationZhang, L.-C. (2022). Graph sampling by lagged random walk. Stat, 11( 1), e444. https://doi.org/10.1002/sta4.444en_US
dc.identifier.issn2049-1573
dc.identifier.urihttps://hdl.handle.net/11250/3055413
dc.description"This is the peer reviewed version of the following article: Zhang, L.-C. (2022). Graph sampling by lagged random walk. Stat, 11( 1), e444, which has been published in final form at https://doi.org/10.1002/sta4.444 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited."en_US
dc.description.abstractWe propose a family of lagged random walk sampling methods in simple undirected graphs, where transition to the next state (i.e., node) depends on both the current and previous states—hence, lagged. The existing random walk sampling methods can be incorporated as special cases. We develop a novel approach to estimation based on lagged random walks at equilibrium, where the target parameter can be any function of values associated with finite-order subgraphs, such as edge, triangle, 4-cycle and others.en_US
dc.language.isoengen_US
dc.publisherWileyen_US
dc.titleGraph sampling by lagged random walken_US
dc.title.alternativeGraph sampling by lagged random walken_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2021 John Wiley & Sons, Ltd.en_US
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Statistikk: 412en_US
dc.source.volume11en_US
dc.source.journalStaten_US
dc.source.issue1en_US
dc.identifier.doi10.1002/sta4.444
dc.identifier.cristin2106108
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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