{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:47:34Z","timestamp":1753876054086,"version":"3.41.2"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2021,9,18]],"date-time":"2021-09-18T00:00:00Z","timestamp":1631923200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research","doi-asserted-by":"crossref","award":["EP\/T018445\/1","EP\/R018472\/1"],"award-info":[{"award-number":["EP\/T018445\/1","EP\/R018472\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,18]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The network disturbance model of P. Doreian (1989), expresses the dependency between observations taken at the vertices of a network by modelling the correlation between neighbouring vertices, using a single correlation parameter $\\rho$. It has been observed that estimation of $\\rho$ in dense graphs, using the method of maximum likelihood, leads to results that can be both biased and very unstable. In this article, we sketch why this is the case, showing that the variability cannot be avoided, no matter how large the network. We also propose a more intuitive estimator of $\\rho$, which shows little bias. The related network effects model is briefly discussed.<\/jats:p>","DOI":"10.1093\/comnet\/cnab028","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T11:37:43Z","timestamp":1631101063000},"source":"Crossref","is-referenced-by-count":1,"title":["Estimating the correlation in network disturbance models"],"prefix":"10.1093","volume":"9","author":[{"given":"A D","family":"Barbour","sequence":"first","affiliation":[{"name":"Institut f\u00fcr Mathematik, Universit\u00e4t Z\u00fcrich, Winterthurertrasse 190, CH-8057 Z\u00fcrich, Switzerland"}]},{"given":"Gesine","family":"Reinert","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Oxford, 24\u201329 St Giles\u2019, Oxford OX1 3LB, UK"}]}],"member":"286","published-online":{"date-parts":[[2021,9,18]]},"reference":[{"key":"2022021418332815000_B1","first-page":"369","article-title":"Network autocorrelation models: problems and prospects","volume-title":"Spatial Statistics: Past, Present, Future","author":"Doreian,","year":"1989"},{"key":"2022021418332815000_B2","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1080\/01621459.1975.10480272","article-title":"Estimation methods for models of spatial interaction","volume":"70","author":"Ord,","year":"1975","journal-title":"J. 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