{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T22:06:20Z","timestamp":1770761180623,"version":"3.50.0"},"reference-count":53,"publisher":"Informa UK Limited","issue":"1","content-domain":{"domain":["www.tandfonline.com"],"crossmark-restriction":true},"short-container-title":["Technometrics"],"published-print":{"date-parts":[[2026,1,2]]},"DOI":"10.1080\/00401706.2025.2561141","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T13:15:53Z","timestamp":1758719753000},"page":"146-158","update-policy":"https:\/\/doi.org\/10.1080\/tandf_crossmark_01","source":"Crossref","is-referenced-by-count":0,"title":["A Scalable Variational Bayes Approach to Fit High-Dimensional Spatial Generalized Linear Mixed Models"],"prefix":"10.1080","volume":"68","author":[{"given":"Jin Hyung","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Statistics, George Mason University","place":["Fairfax"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0658-7458","authenticated-orcid":false,"given":"Ben Seiyon","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Statistics, George Mason University","place":["Fairfax"]}]}],"member":"301","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"e_1_3_2_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1993.10476321"},{"key":"e_1_3_2_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2020.107152"},{"key":"e_1_3_2_4_1","article-title":"\u201cA Conceptual Introduction to Hamiltonian Monte Carlo,\u201d","author":"Betancourt M.","year":"2017","unstructured":"Betancourt, M. (2017), \u201cA Conceptual Introduction to Hamiltonian Monte Carlo,\u201d arXiv preprint arXiv:1701.02434.","journal-title":"arXiv preprint"},{"key":"e_1_3_2_5_1","volume-title":"Pattern Recognition and Machine Learning (Information Science and Statistics)","author":"Bishop C. M.","year":"2006","unstructured":"Bishop, C. M. (2006), Pattern Recognition and Machine Learning (Information Science and Statistics), Berlin, Heidelberg: Springer-Verlag."},{"key":"e_1_3_2_6_1","doi-asserted-by":"publisher","DOI":"10.1214\/06-BA104"},{"key":"e_1_3_2_7_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1285773"},{"key":"e_1_3_2_8_1","doi-asserted-by":"publisher","DOI":"10.1214\/16-SS115"},{"key":"e_1_3_2_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2019.1677471"},{"key":"e_1_3_2_10_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v076.i01"},{"key":"e_1_3_2_11_1","volume-title":"Statistics for Spatial Data","author":"Cressie N.","year":"2015","unstructured":"Cressie, N. (2015), Statistics for Spatial Data, Hoboken, NJ: Wiley."},{"key":"e_1_3_2_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2007.00633.x"},{"key":"e_1_3_2_13_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-040120-020733"},{"key":"e_1_3_2_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(99)00103-6"},{"key":"e_1_3_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2008.2005091"},{"key":"e_1_3_2_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9876.00113"},{"key":"e_1_3_2_17_1","doi-asserted-by":"publisher","DOI":"10.1214\/15-EJS1092"},{"key":"e_1_3_2_18_1","doi-asserted-by":"publisher","DOI":"10.1214\/08-STS257"},{"key":"e_1_3_2_19_1","doi-asserted-by":"publisher","DOI":"10.5194\/tc-7-375-2013"},{"key":"e_1_3_2_20_1","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2018.1425625"},{"key":"e_1_3_2_21_1","article-title":"\u201cIntegrated Non-Factorized Variational Inference,\u201d in","volume":"26","author":"Han S.","year":"2013","unstructured":"Han, S., Liao, X., and Carin, L. (2013), \u201cIntegrated Non-Factorized Variational Inference,\u201d in Advances in Neural Information Processing Systems (Vol. 26).","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/env.2331"},{"key":"e_1_3_2_23_1","doi-asserted-by":"publisher","DOI":"10.1198\/1061860031833"},{"key":"e_1_3_2_24_1","unstructured":"Heaton M. J. Datta A. Finley A. O. Furrer R. Guinness J. Guhaniyogi R. Gerber F. Gramacy R. B. Hammerling D. Katzfuss M. Lindgren F. Nychka D. W. Sun F. and Zammit-Mangion A. (in press) \u201cA Case Study Competition Among Methods for Analyzing Large Spatial Data \u201d JofABE."},{"key":"e_1_3_2_25_1","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2"},{"key":"e_1_3_2_26_1","first-page":"283","volume-title":"Sixth International Workshop on Artificial Intelligence and Statistics","author":"Jaakkola T. S.","year":"1997","unstructured":"Jaakkola, T. S., and Jordan, M. I. (1997), \u201cA Variational Approach to Bayesian Logistic Regression Models and their Extensions,\u201d in Sixth International Workshop on Artificial Intelligence and Statistics, pp. 283\u2013294, PMLR."},{"key":"e_1_3_2_27_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007665907178"},{"key":"e_1_3_2_28_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2015.1123632"},{"key":"e_1_3_2_29_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2021.1933596"},{"key":"e_1_3_2_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/00401706.2022.2115558"},{"key":"e_1_3_2_31_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9787.00135"},{"key":"e_1_3_2_32_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v063.i19"},{"key":"e_1_3_2_33_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2011.00777.x"},{"key":"e_1_3_2_34_1","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.914946"},{"key":"e_1_3_2_35_1","doi-asserted-by":"publisher","DOI":"10.1191\/1471082x02st037oa"},{"key":"e_1_3_2_36_1","doi-asserted-by":"publisher","DOI":"10.1198\/tast.2010.09058"},{"key":"e_1_3_2_37_1","doi-asserted-by":"publisher","DOI":"10.1214\/21-AOAS1524"},{"key":"e_1_3_2_38_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2013.829001"},{"key":"e_1_3_2_39_1","doi-asserted-by":"publisher","DOI":"10.1111\/rssc.12567"},{"key":"e_1_3_2_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-4485-6_7"},{"key":"e_1_3_2_41_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2011.05.021"},{"key":"e_1_3_2_42_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2008.00700.x"},{"key":"e_1_3_2_43_1","doi-asserted-by":"publisher","DOI":"10.1214\/13-BA858"},{"key":"e_1_3_2_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2013.02.002"},{"key":"e_1_3_2_45_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13460"},{"key":"e_1_3_2_46_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-1494-6"},{"key":"e_1_3_2_47_1","unstructured":"Tran M.-N. Nguyen T.-N. and Dao V.-H. (2021) \u201cA Practical Tutorial on Variational Bayes \u201d arXiv preprint arXiv:2103.01327."},{"key":"e_1_3_2_48_1","doi-asserted-by":"publisher","DOI":"10.1561\/2200000001"},{"key":"e_1_3_2_49_1","first-page":"1005","article-title":"\u201cVariational Inference in Nonconjugate Models,\u201d","volume":"14","author":"Wang C.","year":"2013","unstructured":"Wang, C., and Blei, D. M. (2013), \u201cVariational Inference in Nonconjugate Models,\u201d The Journal of Machine Learning Research, 14, 1005\u20131031.","journal-title":"The Journal of Machine Learning Research"},{"key":"e_1_3_2_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.atmosenv.2018.12.004"},{"key":"e_1_3_2_51_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.spasta.2018.03.002"},{"key":"e_1_3_2_52_1","first-page":"5581","volume-title":"International Conference on Machine Learning","author":"Yao Y.","year":"2018","unstructured":"Yao, Y., Vehtari, A., Simpson, D., and Gelman, A. (2018), \u201cYes, But Did It Work?: Evaluating Variational Inference,\u201d in International Conference on Machine Learning, pp. 5581\u20135590, PMLR."},{"key":"e_1_3_2_53_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2002.00129.x"},{"key":"e_1_3_2_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2020.107081"}],"container-title":["Technometrics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.tandfonline.com\/doi\/pdf\/10.1080\/00401706.2025.2561141","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T17:03:41Z","timestamp":1770743021000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/00401706.2025.2561141"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,14]]},"references-count":53,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1,2]]}},"alternative-id":["10.1080\/00401706.2025.2561141"],"URL":"https:\/\/doi.org\/10.1080\/00401706.2025.2561141","relation":{},"ISSN":["0040-1706","1537-2723"],"issn-type":[{"value":"0040-1706","type":"print"},{"value":"1537-2723","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,14]]},"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":"2024-12-31","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-25","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-27","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}