{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T14:20:45Z","timestamp":1763389245797,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T00:00:00Z","timestamp":1565568000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T00:00:00Z","timestamp":1565568000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Adv Data Anal Classif"],"published-print":{"date-parts":[[2020,6]]},"DOI":"10.1007\/s11634-019-00369-4","type":"journal-article","created":{"date-parts":[[2019,8,12]],"date-time":"2019-08-12T16:07:51Z","timestamp":1565626071000},"page":"235-260","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Seemingly unrelated clusterwise linear regression"],"prefix":"10.1007","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9161-9671","authenticated-orcid":false,"given":"Giuliano","family":"Galimberti","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7575-892X","authenticated-orcid":false,"given":"Gabriele","family":"Soffritti","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,12]]},"reference":[{"key":"369_CR1","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780199219148.001.0001","volume-title":"Statistical modelling in R","author":"M Aitkin","year":"2009","unstructured":"Aitkin M, Francis B, Hinde J, Darnell R (2009) Statistical modelling in R. Oxford University Press, New York"},{"key":"369_CR2","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1080\/00401706.1980.10486163","volume":"22","author":"M Aitkin","year":"1980","unstructured":"Aitkin M, Tunnicliffe Wilson G (1980) Mixture models, outliers, and the EM algorithm. Technometrics 22:325\u2013331","journal-title":"Technometrics"},{"key":"369_CR3","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1080\/00045608.2010.544965","volume":"101","author":"IG Baird","year":"2011","unstructured":"Baird IG, Quastel N (2011) Dolphin-safe tuna from California to Thailand: localisms in environmental certification of global commodity networks. Ann Assoc Am Geogr 101:337\u2013355","journal-title":"Ann Assoc Am Geogr"},{"key":"369_CR4","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1016\/j.csda.2004.04.005","volume":"48","author":"F Bartolucci","year":"2005","unstructured":"Bartolucci F, Scaccia L (2005) The use of mixtures for dealing with non-normal regression errors. Comput Stat Data Anal 48:821\u2013834","journal-title":"Comput Stat Data Anal"},{"key":"369_CR5","doi-asserted-by":"crossref","first-page":"548","DOI":"10.1016\/j.meatsci.2012.05.025","volume":"92","author":"VAP Cadavez","year":"2012","unstructured":"Cadavez VAP, Hennningsen A (2012) The use of seemingly unrelated regression (SUR) to predict the carcass composition of lambs. Meat Sci 92:548\u2013553","journal-title":"Meat Sci"},{"key":"369_CR6","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/0031-3203(94)00125-6","volume":"28","author":"G Celeux","year":"1995","unstructured":"Celeux G, Govaert G (1995) Gaussian parsimonious clustering models. Pattern Recognit 28:781\u2013793","journal-title":"Pattern Recognit"},{"key":"369_CR7","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1257\/000282803321455142","volume":"93","author":"JA Chevalier","year":"2003","unstructured":"Chevalier JA, Kashyap AK, Rossi PE (2003) Why don\u2019t prices rise during periods of peak demand? Evidence from scanner data. Am Econ Rev 93:15\u201337","journal-title":"Am Econ Rev"},{"key":"369_CR8","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/978-3-319-17377-1_9","volume-title":"Advances in statistical models for data analysis","author":"UJ Dang","year":"2015","unstructured":"Dang UJ, McNicholas PD (2015) Families of parsimonious finite mixtures of regression models. In: Morlini I, Minerva T, Vichi M (eds) Advances in statistical models for data analysis. Springer, Cham, pp 73\u201384"},{"key":"369_CR9","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1093\/biomet\/56.3.463","volume":"56","author":"NE Day","year":"1969","unstructured":"Day NE (1969) Estimating the components of a mixture of normal distributions. Biometrika 56:463\u2013474","journal-title":"Biometrika"},{"key":"369_CR10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"AP Dempster","year":"1977","unstructured":"Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood for incomplete data via the EM algorithm. J R Stat Soc B 39:1\u201322","journal-title":"J R Stat Soc B"},{"key":"369_CR11","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1007\/BF01897167","volume":"5","author":"WS De Sarbo","year":"1988","unstructured":"De Sarbo WS, Cron WL (1988) A maximum likelihood methodology for clusterwise linear regression. J Classif 5:249\u2013282","journal-title":"J Classif"},{"key":"369_CR12","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/0167-9473(89)90043-1","volume":"8","author":"RD De Veaux","year":"1989","unstructured":"De Veaux RD (1989) Mixtures of linear regressions. Comput Stat Data Anal 8:227\u2013245","journal-title":"Comput Stat Data Anal"},{"key":"369_CR13","first-page":"1","volume":"11","author":"C Ding","year":"2006","unstructured":"Ding C (2006) Using regression mixture analysis in educational research. Pract Assess Res Eval 11:1\u201311","journal-title":"Pract Assess Res Eval"},{"key":"369_CR14","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1111\/j.1475-4932.1982.tb00382.x","volume":"58","author":"WA Donnelly","year":"1982","unstructured":"Donnelly WA (1982) The regional demand for petrol in Australia. Econ Rec 58:317\u2013327","journal-title":"Econ Rec"},{"key":"369_CR15","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.1111\/j.1741-3737.2012.01012.x","volume":"74","author":"WJ Dyer","year":"2012","unstructured":"Dyer WJ, Pleck J, McBride B (2012) Using mixture regression to identify varying effects: a demonstration with paternal incarceration. J Marriage Fam 74:1129\u20131148","journal-title":"J Marriage Fam"},{"key":"369_CR16","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1007\/978-3-319-63712-9_14","volume-title":"Smart cities, green technologies, and intelligent transport systems","author":"M Elhenawy","year":"2017","unstructured":"Elhenawy M, Rakha H, Chen H (2017) An automatic traffic congestion identification algorithm based on mixture of linear regressions. In: Helfert M, Klein C, Donnellan B, Gusikhin O (eds) Smart cities, green technologies, and intelligent transport systems. Springer, Cham, pp 242\u2013256"},{"key":"369_CR17","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1198\/016214502760047131","volume":"97","author":"C Fraley","year":"2002","unstructured":"Fraley C, Raftery AE (2002) Model-based clustering, discriminant analysis and density estimation. J Am Stat Assoc 97:611\u2013631","journal-title":"J Am Stat Assoc"},{"key":"369_CR18","volume-title":"Finite mixture and Markov switching models","author":"S Fr\u00fchwirth-Schnatter","year":"2006","unstructured":"Fr\u00fchwirth-Schnatter S (2006) Finite mixture and Markov switching models. Springer, New York"},{"key":"369_CR19","doi-asserted-by":"crossref","first-page":"1025","DOI":"10.1007\/s11222-015-9587-0","volume":"26","author":"G Galimberti","year":"2016","unstructured":"Galimberti G, Scardovi E, Soffritti G (2016) Using mixtures in seemingly unrelated linear regression models with non-normal errors. Stat Comput 26:1025\u20131038","journal-title":"Stat Comput"},{"key":"369_CR20","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1111\/j.1467-9787.1984.tb01045.x","volume":"24","author":"S Giles","year":"1984","unstructured":"Giles S, Hampton P (1984) Regional production relationships during the industrialization of New Zealand, 1935\u20131948. Reg Sci 24:519\u2013533","journal-title":"Reg Sci"},{"issue":"4","key":"369_CR21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i04","volume":"28","author":"B Gr\u00fcn","year":"2008","unstructured":"Gr\u00fcn B, Leisch F (2008) FlexMix version 2: finite mixtures with concomitant variables and varying and constant parameters. J Stat Softw 28(4):1\u201335","journal-title":"J Stat Softw"},{"key":"369_CR22","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s003570000022","volume":"17","author":"C Hennig","year":"2000","unstructured":"Hennig C (2000) Identifiability of models for clusterwise linear regression. J Classif 17:273\u2013296","journal-title":"J Classif"},{"issue":"4","key":"369_CR23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v023.i04","volume":"23","author":"A Henningsen","year":"2007","unstructured":"Henningsen A, Hamann JD (2007) systemfit: a package for estimating systems of simultaneous equations in R. J Stat Softw 23(4):1\u201340","journal-title":"J Stat Softw"},{"key":"369_CR24","first-page":"995","volume":"3","author":"DW Hosmer","year":"1974","unstructured":"Hosmer DW (1974) Maximum likelihood estimates of the parameters of a mixture of two regression lines. Commun Stat Theory Methods 3:995\u20131006","journal-title":"Commun Stat Theory Methods"},{"key":"369_CR25","doi-asserted-by":"crossref","first-page":"1715","DOI":"10.1016\/j.csda.2010.10.026","volume":"55","author":"S Ingrassia","year":"2011","unstructured":"Ingrassia S, Rocci R (2011) Degeneracy of the EM algorithm for the MLE of multivariate Gaussian mixtures and dynamic constraints. Comput Stat Data Anal 55:1715\u20131725","journal-title":"Comput Stat Data Anal"},{"key":"369_CR26","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1111\/j.1467-842X.1992.tb01356.x","volume":"34","author":"PN Jones","year":"1992","unstructured":"Jones PN, McLachlan GJ (1992) Fitting finite mixture models in a regression context. Aust J Stat 34:233\u2013240","journal-title":"Aust J Stat"},{"key":"369_CR27","doi-asserted-by":"crossref","unstructured":"Keshavarzi S, Ayatollahi SMT, Zare N, Pakfetrat M (2012) Application of seemingly unrelated regression in medical data with intermittently observed time-dependent covariates. Comput Math Methods Med 2012, 821643","DOI":"10.1155\/2012\/821643"},{"key":"369_CR28","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1214\/aoms\/1177728066","volume":"27","author":"J Kiefer","year":"1956","unstructured":"Kiefer J, Wolfowitz J (1956) Consistency of the maximum likelihood estimator in the presence of infinitely many nuisance parameters. Ann Math Stat 27:887\u2013906","journal-title":"Ann Math Stat"},{"key":"369_CR29","doi-asserted-by":"crossref","DOI":"10.1007\/b98855","volume-title":"Elements of large-sample theory","author":"EL Lehmann","year":"1999","unstructured":"Lehmann EL (1999) Elements of large-sample theory. Springer, New York"},{"key":"369_CR30","volume-title":"Matrix differential calculus with applications in statistics and econometrics","author":"JR Magnus","year":"1988","unstructured":"Magnus JR, Neudecker H (1988) Matrix differential calculus with applications in statistics and econometrics. Wiley, New York"},{"key":"369_CR31","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1111\/j.1541-0420.2008.01160.x","volume":"65","author":"C Maugis","year":"2009","unstructured":"Maugis C, Celeux G, Martin-Magniette M-L (2009) Variable selection for clustering with Gaussian mixture models. Biometrics 65:701\u2013709","journal-title":"Biometrics"},{"key":"369_CR32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.chiabu.2016.06.010","volume":"58","author":"SE McDonald","year":"2016","unstructured":"McDonald SE, Shin S, Corona R et al (2016) Children exposed to intimate partner violence: identifying differential effects of family environment on children\u2019s trauma and psychopathology symptoms through regression mixture models. Child Abus Negl 58:1\u201311","journal-title":"Child Abus Negl"},{"key":"369_CR33","doi-asserted-by":"crossref","DOI":"10.1002\/0471721182","volume-title":"Finite mixture models","author":"GJ McLachlan","year":"2000","unstructured":"McLachlan GJ, Peel D (2000) Finite mixture models. Wiley, New York"},{"key":"369_CR34","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1016\/S1573-4412(05)80005-4","volume-title":"Handbook of econometrics","author":"WK Newey","year":"1994","unstructured":"Newey WK, McFadden D (1994) Large sample estimation and hypothesis testing. In: Griliches Z, Engle R, Intriligator MD, McFadden D (eds) Handbook of econometrics, vol 4. Elsevier, Amsterdam, pp 2111\u20132245"},{"key":"369_CR35","unstructured":"Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2017) nlme: linear and nonlinear mixed effects models. R package version 3.1-131"},{"key":"369_CR36","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1080\/01621459.1978.10480085","volume":"73","author":"RE Quandt","year":"1978","unstructured":"Quandt RE, Ramsey JB (1978) Estimating mixtures of normal distributions and switching regressions. J Am Stat Assoc 73:730\u2013738","journal-title":"J Am Stat Assoc"},{"key":"369_CR37","unstructured":"R Core Team (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http:\/\/www.R-project.org"},{"key":"369_CR38","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s11634-016-0279-1","volume":"12","author":"R Rocci","year":"2018","unstructured":"Rocci R, Gattone SA, Di Mari R (2018) A data driven equivariant approach to constrained Gaussian mixture modeling. Adv Data Anal Classif 12:235\u2013260","journal-title":"Adv Data Anal Classif"},{"key":"369_CR39","unstructured":"Rossi PE (2012) bayesm: Bayesian inference for marketing\/micro-econometrics. R package version 2.2-5. http:\/\/CRAN.R-project.org\/package=bayesm"},{"key":"369_CR40","doi-asserted-by":"crossref","DOI":"10.1002\/0470863692","volume-title":"Bayesian statistics and marketing","author":"PE Rossi","year":"2005","unstructured":"Rossi PE, Allenby GM, McCulloch R (2005) Bayesian statistics and marketing. Wiley, Chichester"},{"key":"369_CR41","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","volume":"6","author":"G Schwarz","year":"1978","unstructured":"Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461\u2013464","journal-title":"Ann Stat"},{"issue":"1","key":"369_CR42","first-page":"205","volume":"8","author":"L Scrucca","year":"2017","unstructured":"Scrucca L, Fop M, Murphy TB, Raftery AE (2017) mclust5: clustering, classification and density estimation using Gaussian finite mixture models. R J 8(1):205\u2013223","journal-title":"R J"},{"key":"369_CR43","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1007\/s11222-010-9190-3","volume":"21","author":"G Soffritti","year":"2011","unstructured":"Soffritti G, Galimberti G (2011) Multivariate linear regression with non-normal errors: a solution based on mixture models. Stat Comput 21:523\u2013536","journal-title":"Stat Comput"},{"key":"369_CR44","volume-title":"Seemingly unrelated regression equations models","author":"VK Srivastava","year":"1987","unstructured":"Srivastava VK, Giles DEA (1987) Seemingly unrelated regression equations models. Marcel Dekker, New York"},{"key":"369_CR45","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1080\/14697680802595635","volume":"9","author":"A Tashman","year":"2009","unstructured":"Tashman A, Frey RJ (2009) Modeling risk in arbitrage strategies using finite mixtures. Quant Finance 9:495\u2013503","journal-title":"Quant Finance"},{"key":"369_CR46","first-page":"371","volume":"49","author":"TR Turner","year":"2000","unstructured":"Turner TR (2000) Estimating the propagation rate of a viral infection of potato plants via mixtures of regressions. Appl Stat 49:371\u2013384","journal-title":"Appl Stat"},{"key":"369_CR47","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1177\/0013164414554931","volume":"75","author":"ML Van Horn","year":"2015","unstructured":"Van Horn ML, Jaki T, Masyn K et al (2015) Evaluating differential effects using regression interactions and regression mixture models. Educ Psychol Meas 75:677\u2013714","journal-title":"Educ Psychol Meas"},{"key":"369_CR48","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1111\/j.1467-9787.1982.tb00753.x","volume":"22","author":"EN White","year":"1982","unstructured":"White EN, Hewings GJD (1982) Space-time employment modelling: some results using seemingly unrelated regression estimators. J Reg Sci 22:283\u2013302","journal-title":"J Reg Sci"},{"key":"369_CR49","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1080\/00949655.2013.859259","volume":"85","author":"W Yao","year":"2015","unstructured":"Yao W (2015) Label switching and its solutions for frequentist mixture models. J Stat Comput Simul 85:1000\u20131012","journal-title":"J Stat Comput Simul"},{"key":"369_CR50","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1080\/01621459.1962.10480664","volume":"57","author":"A Zellner","year":"1962","unstructured":"Zellner A (1962) An efficient method of estimating seemingly unrelated regression equations and testst for aggregation bias. J Am Stat Assoc 57:348\u2013368","journal-title":"J Am Stat Assoc"}],"container-title":["Advances in Data Analysis and Classification"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-019-00369-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11634-019-00369-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-019-00369-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,21]],"date-time":"2024-07-21T22:52:52Z","timestamp":1721602372000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11634-019-00369-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,12]]},"references-count":50,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,6]]}},"alternative-id":["369"],"URL":"https:\/\/doi.org\/10.1007\/s11634-019-00369-4","relation":{},"ISSN":["1862-5347","1862-5355"],"issn-type":[{"type":"print","value":"1862-5347"},{"type":"electronic","value":"1862-5355"}],"subject":[],"published":{"date-parts":[[2019,8,12]]},"assertion":[{"value":"29 November 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 August 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 August 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}