{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T17:17:12Z","timestamp":1773335832419,"version":"3.50.1"},"reference-count":55,"publisher":"Informa UK Limited","issue":"3","funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["DMS-2210672, DMS-2220840"],"award-info":[{"award-number":["DMS-2210672, DMS-2220840"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000065","name":"National Institute Of Neurological Disorders And Stroke","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000065","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01NS131604"],"award-info":[{"award-number":["R01NS131604"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Technometrics"],"published-print":{"date-parts":[[2024,7,2]]},"DOI":"10.1080\/00401706.2024.2321930","type":"journal-article","created":{"date-parts":[[2024,3,4]],"date-time":"2024-03-04T19:32:37Z","timestamp":1709580757000},"page":"422-437","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":5,"title":["Covariate-Dependent Clustering of Undirected Networks with Brain-Imaging Data"],"prefix":"10.1080","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9335-0952","authenticated-orcid":false,"given":"Sharmistha","family":"Guha","sequence":"first","affiliation":[{"name":"Department of Statistics, Texas A & M University, College Station, TX"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajarshi","family":"Guhaniyogi","sequence":"additional","affiliation":[{"name":"Department of Statistics, Texas A & M University, College Station, TX"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2024,3,25]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.3150\/bj\/1068128979"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cub.2017.04.051"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrn2575"},{"key":"e_1_3_3_5_1","volume-title":"Twenty-Third International Joint Conference on Artificial Intelligence","author":"Cao X.","year":"2013","unstructured":"Cao, X., Wei, X., Han, Y., Yang, Y., and Lin, D. (2013), \u201cRobust Tensor Clustering with Non-greedy Maximization,\u201d in Twenty-Third International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1207\/s15326934crj1701_4"},{"key":"e_1_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.08.008"},{"key":"e_1_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.948181"},{"key":"e_1_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12540"},{"key":"e_1_3_3_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2006.01.021"},{"key":"e_1_3_3_11_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asm071"},{"key":"e_1_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1995.10476550"},{"key":"e_1_3_3_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/08964289.1991.9935164"},{"key":"e_1_3_3_14_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1986.10478342"},{"key":"e_1_3_3_15_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2019.1708463"},{"key":"e_1_3_3_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/85.1.1"},{"key":"e_1_3_3_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2020.1784799"},{"key":"e_1_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2020.1772079"},{"key":"e_1_3_3_19_1","doi-asserted-by":"publisher","DOI":"10.1214\/21-BA1280"},{"key":"e_1_3_3_20_1","first-page":"1","article-title":"\u201cBayesian Tensor Regression,\u201d","volume":"18","author":"Guhaniyogi R.","year":"2017","unstructured":"Guhaniyogi, R., Qamar, S., and Dunson, D. B. (2017), \u201cBayesian Tensor Regression,\u201d Journal of Machine Learning Research, 18, 1\u201331.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_3_21_1","first-page":"923","article-title":"\u201cDirichlet Process Mixtures of Generalized Linear Models,\u201d","volume":"12","author":"Hannah L. A.","year":"2011","unstructured":"Hannah, L. A., Blei, D. M., and Powell, W. B. (2011), \u201cDirichlet Process Mixtures of Generalized Linear Models,\u201d Journal of Machine Learning Research, 12, 923\u20131953.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_3_22_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214504000001015"},{"key":"e_1_3_3_23_1","doi-asserted-by":"publisher","DOI":"10.5705\/ss.2010.051"},{"key":"e_1_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214502388618906"},{"key":"e_1_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2009.tm08024"},{"key":"e_1_3_3_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01908075"},{"key":"e_1_3_3_27_1","doi-asserted-by":"publisher","DOI":"10.1198\/106186002411"},{"key":"e_1_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.1002\/hbm.20874"},{"key":"e_1_3_3_29_1","unstructured":"Kiar G. Gray Roncal W. Mhembere D. Bridgeford E. Burns R. and Vogelstein J. (2016) \u201cndmg: Neurodata\u2019s MRI Graphs Pipeline.\u201d"},{"key":"e_1_3_3_30_1","unstructured":"Kim Y. and Levina E. (2019) \u201cGraph-Aware Modeling of Brain Connectivity Networks \u201d arXiv preprint arXiv:1903.02129."},{"key":"e_1_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/0028-3932(81)90016-6"},{"key":"e_1_3_3_32_1","doi-asserted-by":"publisher","DOI":"10.1198\/106186007X238855"},{"key":"e_1_3_3_33_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2010.01392.x"},{"key":"e_1_3_3_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2014.2373411"},{"key":"e_1_3_3_35_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0073186"},{"key":"e_1_3_3_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.04.084"},{"key":"e_1_3_3_37_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.11.059"},{"key":"e_1_3_3_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/0028-3932(85)90023-5"},{"key":"e_1_3_3_39_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/83.1.67"},{"key":"e_1_3_3_40_1","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753208735"},{"key":"e_1_3_3_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.116611"},{"key":"e_1_3_3_42_1","first-page":"1867","article-title":"\u201cLow-Rank Regression with Tensor Responses,\u201d","author":"Rabusseau G.","year":"2016","unstructured":"Rabusseau, G., and Kadri, H. (2016), \u201cLow-Rank Regression with Tensor Responses,\u201d in Advances in Neural Information Processing Systems, pp. 1867\u20131875.","journal-title":"in Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainresbull.2007.02.008"},{"key":"e_1_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1214\/19-AOAS1252"},{"key":"e_1_3_3_45_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asn054"},{"key":"e_1_3_3_46_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2011.00781.x"},{"key":"e_1_3_3_47_1","doi-asserted-by":"publisher","DOI":"10.1089\/brain.2012.0080"},{"key":"e_1_3_3_48_1","first-page":"639","article-title":"\u201cA Constructive Definition of Dirichlet Priors,\u201d","volume":"4","author":"Sethuraman J.","year":"1994","unstructured":"Sethuraman, J. (1994), \u201cA Constructive Definition of Dirichlet Priors,\u201d Statistica Sinica, 4, 639\u2013650.","journal-title":"Statistica Sinica"},{"key":"e_1_3_3_49_1","first-page":"1829","article-title":"\u201cNonlinear Models Using Dirichlet Process Mixtures,\u201d","volume":"10","author":"Shahbaba B.","year":"2009","unstructured":"Shahbaba, B., and Neal, R. (2009), \u201cNonlinear Models Using Dirichlet Process Mixtures,\u201d Journal of Machine Learning Research, 10, 1829\u20131850.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_3_50_1","doi-asserted-by":"publisher","DOI":"10.1038\/srep42911"},{"key":"e_1_3_3_51_1","doi-asserted-by":"publisher","DOI":"10.1227\/00006123-198507000-00007"},{"key":"e_1_3_3_52_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btx050"},{"key":"e_1_3_3_53_1","first-page":"2559","article-title":"\u201cGeneral Tensor Spectral Co-clustering for Higher-Order Data,\u201d in","author":"Wu T.","year":"2016","unstructured":"Wu, T., Benson, A. R., and Gleich, D. F. (2016), \u201cGeneral Tensor Spectral Co-clustering for Higher-Order Data,\u201d in Advances in Neural Information Processing Systems, pp. 2559\u20132567.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_3_54_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-77004-6_11"},{"key":"e_1_3_3_55_1","doi-asserted-by":"publisher","DOI":"10.1093\/biostatistics\/kxz057"},{"key":"e_1_3_3_56_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2015.1131699"}],"container-title":["Technometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/00401706.2024.2321930","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T14:30:46Z","timestamp":1727188246000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00401706.2024.2321930"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,25]]},"references-count":55,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,7,2]]}},"alternative-id":["10.1080\/00401706.2024.2321930"],"URL":"https:\/\/doi.org\/10.1080\/00401706.2024.2321930","relation":{},"ISSN":["0040-1706","1537-2723"],"issn-type":[{"value":"0040-1706","type":"print"},{"value":"1537-2723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,25]]},"assertion":[{"value":"The publishing and review policy for this title is described in its Aims & Scope.","order":1,"name":"peerreview_statement","label":"Peer Review Statement"},{"value":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=utch20","URL":"http:\/\/www.tandfonline.com\/action\/journalInformation?show=aimsScope&journalCode=utch20","order":2,"name":"aims_and_scope_url","label":"Aim & Scope"},{"value":"2022-01-09","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-02-14","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-02-17","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-03-25","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}