{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T23:25:32Z","timestamp":1762298732801},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2017,12,15]],"date-time":"2017-12-15T00:00:00Z","timestamp":1513296000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"ERDF-European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation COMPETE 2020 Programme","award":["project POCI-01-0145-FEDER-006961"],"award-info":[{"award-number":["project POCI-01-0145-FEDER-006961"]}]},{"name":"Portuguese Foundation for Science and Technology","award":["UID\/GES\/00731\/2013","project UID\/EEA\/50014\/2013"],"award-info":[{"award-number":["UID\/GES\/00731\/2013","project UID\/EEA\/50014\/2013"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Adv Data Anal Classif"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s11634-017-0305-y","type":"journal-article","created":{"date-parts":[[2017,12,15]],"date-time":"2017-12-15T12:21:34Z","timestamp":1513340494000},"page":"785-822","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Outlier detection in interval data"],"prefix":"10.1007","volume":"12","author":[{"given":"A. Pedro","family":"Duarte Silva","sequence":"first","affiliation":[]},{"given":"Peter","family":"Filzmoser","sequence":"additional","affiliation":[]},{"given":"Paula","family":"Brito","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,12,15]]},"reference":[{"issue":"462","key":"305_CR1","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1198\/016214503000242","volume":"98","author":"B Billard","year":"2003","unstructured":"Billard B, Diday E (2003) From the statistics of data to the statistics of knowledge: symbolic data analysis. J Am Stat Assoc 98(462):470\u2013487","journal-title":"J Am Stat Assoc"},{"key":"305_CR2","volume-title":"Analysis of symbolic data. Exploratory methods for extracting statistical information from complex data","author":"H-H Bock","year":"2000","unstructured":"Bock H-H, Diday E (2000) Analysis of symbolic data. Exploratory methods for extracting statistical information from complex data. Springer, Heidelberg"},{"issue":"4","key":"305_CR3","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1002\/widm.1133","volume":"4","author":"P Brito","year":"2014","unstructured":"Brito P (2014) Symbolic data analysis: another look at the interaction of data mining and statistics. WIREs Data Min Knowl Discov 4(4):281\u2013295","journal-title":"WIREs Data Min Knowl Discov"},{"issue":"1","key":"305_CR4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/02664763.2011.575125","volume":"39","author":"P Brito","year":"2012","unstructured":"Brito P, Duarte Silva AP (2012) Modelling interval data with Normal and Skew-Normal distributions. J Appl Stat 39(1):3\u201320","journal-title":"J Appl Stat"},{"issue":"489","key":"305_CR5","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1198\/jasa.2009.tm09147","volume":"105","author":"A Cerioli","year":"2010","unstructured":"Cerioli A (2010) Multivariate outlier detection with high-breakdown estimators. J Am Stat Assoc 105(489):147\u2013156","journal-title":"J Am Stat Assoc"},{"issue":"2","key":"305_CR6","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/s00180-006-0261-z","volume":"21","author":"FAT Carvalho De","year":"2006","unstructured":"De Carvalho FAT, Brito P, Bock H-H (2006) Dynamic clustering for interval data based on $$L_2$$ L 2 distance. Comput Stat 21(2):231\u2013250","journal-title":"Comput Stat"},{"issue":"7","key":"305_CR7","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1016\/j.patcog.2008.11.016","volume":"42","author":"FAT Carvalho De","year":"2009","unstructured":"De Carvalho FAT, Lechevallier Y (2009) Partitional clustering algorithms for symbolic interval data based on single adaptive distances. Pattern Recogn 42(7):1223\u20131236","journal-title":"Pattern Recogn"},{"issue":"3","key":"305_CR8","doi-asserted-by":"crossref","first-page":"1118","DOI":"10.1016\/j.ejor.2016.09.006","volume":"258","author":"S Dias","year":"2017","unstructured":"Dias S, Brito P (2017) Off the beaten track: a new linear model for interval data. Eur J Oper Res 258(3):1118\u20131130","journal-title":"Eur J Oper Res"},{"key":"305_CR9","volume-title":"Symbolic data analysis and the SODAS software","author":"E Diday","year":"2008","unstructured":"Diday E, Noirhomme-Fraiture M (2008) Symbolic data analysis and the SODAS software. Wiley, Chichester"},{"issue":"2","key":"305_CR10","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1002\/sam.10118","volume":"4","author":"A Douzal-Chouakria","year":"2011","unstructured":"Douzal-Chouakria A, Billard L, Diday E (2011) Principal component analysis for interval-valued observations. Stat Anal Data Min 4(2):229\u2013246","journal-title":"Stat Anal Data Min"},{"key":"305_CR11","unstructured":"Duarte Silva AP, Brito P (2017) MAINT.DATA: Model and analyze interval data. R Package,version 1.2.0. http:\/\/cran.r-project.org\/web\/packages\/MAINT.Data\/index.html"},{"issue":"3","key":"305_CR12","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1007\/s00357-015-9189-8","volume":"32","author":"AP Duarte Silva","year":"2015","unstructured":"Duarte Silva AP, Brito P (2015) Discriminant analysis of interval data: an assessment of parametric and distance-based approaches. J Classif 32(3):516\u2013541","journal-title":"J Classif"},{"key":"305_CR13","unstructured":"Filzmoser P (2004) A multivariate outlier detection method. In: S. Aivazian, P. Filzmoser and Yu. Kharin, editors, In Proceedings of the 7th international conference on computer data analysis and modeling, vol 1, 18\u201322, Belarusian State University, Minsk"},{"key":"305_CR14","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1016\/j.cageo.2004.11.013","volume":"31","author":"P Filzmoser","year":"2005","unstructured":"Filzmoser P, Reimann C, Garrett RG (2005) Multivariate outlier detection in exploration geochemistry. Comput Geosci 31:579\u2013587","journal-title":"Comput Geosci"},{"issue":"3","key":"305_CR15","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/S0167-9473(97)00011-X","volume":"25","author":"AS Hadi","year":"1997","unstructured":"Hadi AS, Luce\u00f1o A (1997) Maximum trimmed likelihood estimators: a unified approach, examples, and algorithms. Comput Stat Data Anal 25(3):251\u2013272","journal-title":"Comput Stat Data Anal"},{"key":"305_CR16","doi-asserted-by":"crossref","first-page":"910","DOI":"10.1198\/106186005X78585","volume":"14","author":"J Hardin","year":"2005","unstructured":"Hardin J, Rocke DM (2005) The distribution of robust distances. J Comput Gr Stat 14:910\u2013927","journal-title":"J Comput Gr Stat"},{"issue":"1","key":"305_CR17","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1214\/088342307000000087","volume":"23","author":"M Hubert","year":"2008","unstructured":"Hubert M, Rousseeuw PJ, Van Aelst S (2008) High-breakdown robust multivariate methods. Stat Sci 23(1):92\u2013119","journal-title":"Stat Sci"},{"issue":"2","key":"305_CR18","doi-asserted-by":"crossref","first-page":"151","DOI":"10.32614\/RJ-2014-031","volume":"6","author":"S Korkmaz","year":"2014","unstructured":"Korkmaz S, Goksuluk D, Zararsiz G (2014) MVN: an R package for assessing multivariate normality. R J 6(2):151\u2013162","journal-title":"R J"},{"key":"305_CR19","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1016\/j.jspi.2010.11.016","volume":"141","author":"J Le-Rademacher","year":"2011","unstructured":"Le-Rademacher J, Billard L (2011) Likelihood functions and some maximum likelihood estimators for symbolic data. J Stat Plan Inference 141:1593\u20131602","journal-title":"J Stat Plan Inference"},{"issue":"2","key":"305_CR20","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1080\/10618600.2012.679895","volume":"21","author":"J Le-Rademacher","year":"2012","unstructured":"Le-Rademacher J, Billard L (2012) Symbolic covariance principal component analysis and visualization for interval-valued data. J Comput Gr Stat 21(2):413\u2013432","journal-title":"J Comput Gr Stat"},{"key":"305_CR21","doi-asserted-by":"crossref","unstructured":"Li S, Lee R, Lang S-D (2006) Detecting outliers in interval data. In Proceedings of the 44th annual southeast regional conference, ACM, pp 290\u2013295","DOI":"10.1145\/1185448.1185514"},{"issue":"3","key":"305_CR22","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1016\/j.csda.2007.04.014","volume":"52","author":"Neto E Lima","year":"2008","unstructured":"Lima Neto E, De Carvalho FAT (2008) Centre and range method for fitting a linear regression model to symbolic interval data. Comput Stat Data Anal 52(3):1500\u20131515","journal-title":"Comput Stat Data Anal"},{"issue":"2","key":"305_CR23","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.csda.2009.08.010","volume":"54","author":"Neto E Lima","year":"2010","unstructured":"Lima Neto E, De Carvalho FAT (2010) Constrained linear regression models for symbolic interval-valued variables. Comput Stat Data Anal 54(2):333\u2013347","journal-title":"Comput Stat Data Anal"},{"issue":"11","key":"305_CR24","doi-asserted-by":"crossref","first-page":"1727","DOI":"10.1080\/00949655.2010.500470","volume":"81","author":"Neto E Lima","year":"2011","unstructured":"Lima Neto E, Cordeiro GM, De Carvalho FAT (2011) Bivariate symbolic regression models for interval-valued variables. J Stat Comput Simul 81(11):1727\u20131744","journal-title":"J Stat Comput Simul"},{"issue":"1","key":"305_CR25","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.csda.2006.12.024","volume":"52","author":"N Neykov","year":"2007","unstructured":"Neykov N, Filzmoser P, Dimova R, Neytchev P (2007) Robust fitting of mixtures using the trimmed likelihood estimator. Comput Stat Data Anal 52(1):299\u2013308","journal-title":"Comput Stat Data Anal"},{"key":"305_CR26","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1007\/978-3-642-57338-5_24","volume-title":"Developments in robust statistics","author":"NM Neykov","year":"2003","unstructured":"Neykov NM, M\u00fcller CH (2003) Breakdown point and computation of trimmed likelihood estimators in generalized linear models. In: Dutter R, Filzmoser P, Gather U, Rousseeuw PJ (eds) Developments in robust statistics. Physica-Verlag, Heidelberg, pp 277\u2013286"},{"issue":"2","key":"305_CR27","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1002\/sam.10112","volume":"4","author":"M Noirhomme-Fraiture","year":"2011","unstructured":"Noirhomme-Fraiture M, Brito P (2011) Far beyond the classical data models: symbolic data analysis. Stat Anal Data Min 4(2):157\u2013170","journal-title":"Stat Anal Data Min"},{"issue":"1\u20132","key":"305_CR28","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1007\/s001840200191","volume":"55","author":"G Pison","year":"2002","unstructured":"Pison G, Van Aelst S, Willems G (2002) Small sample corrections for LTS and MCD. Metrika 55(1\u20132):111\u2013123","journal-title":"Metrika"},{"key":"305_CR29","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.ins.2016.08.068","volume":"372","author":"AB Ramos-Guajardo","year":"2016","unstructured":"Ramos-Guajardo AB, Grzegorzewski P (2016) Distance-based linear discriminant analysis for interval-valued data. Inf Sci 372:591\u2013607","journal-title":"Inf Sci"},{"issue":"388","key":"305_CR30","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1080\/01621459.1984.10477105","volume":"79","author":"PJ Rousseeuw","year":"1984","unstructured":"Rousseeuw PJ (1984) Least median of squares regression. J Am Stat Assoc 79(388):871\u2013880","journal-title":"J Am Stat Assoc"},{"key":"305_CR31","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/978-94-009-5438-0_20","volume":"8","author":"PJ Rousseeuw","year":"1985","unstructured":"Rousseeuw PJ (1985) Multivariate estimation with high breakdown point. Math Stat Appl 8:283\u2013297","journal-title":"Math Stat Appl"},{"issue":"3","key":"305_CR32","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1080\/00401706.1999.10485670","volume":"41","author":"PJ Rousseeuw","year":"1999","unstructured":"Rousseeuw PJ, Van Driessen K (1999) A fast algorithm for the minimum covariance determinant estimator. Technometrics 41(3):212\u2013223","journal-title":"Technometrics"},{"issue":"411","key":"305_CR33","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1080\/01621459.1990.10474920","volume":"85","author":"PJ Rousseeuw","year":"1990","unstructured":"Rousseeuw PJ, Van Zomeren BC (1990) Unmasking multivariate outliers and leverage points. J Am Stat Assoc 85(411):633\u2013639","journal-title":"J Am Stat Assoc"},{"key":"305_CR34","volume-title":"Information retrieval","author":"CJ Rijsbergen Van","year":"1979","unstructured":"Van Rijsbergen CJ (1979) Information retrieval, 2nd edn. Butterworth, London","edition":"2"},{"key":"305_CR35","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1080\/02331889808802657","volume":"32","author":"DL Vandev","year":"1998","unstructured":"Vandev DL, Neykov NM (1998) About regression estimators with high breakdown point. Statistics 32:111\u2013129","journal-title":"Statistics"},{"issue":"2","key":"305_CR36","first-page":"39","volume":"5","author":"D Viattchenin","year":"2012","unstructured":"Viattchenin D (2012) Detecting outliers in interval-valued data using heuristic possibilistic clustering. J Comput Sci Control Syst 5(2):39\u201344","journal-title":"J Comput Sci Control Syst"}],"container-title":["Advances in Data Analysis and Classification"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11634-017-0305-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-017-0305-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11634-017-0305-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,8]],"date-time":"2019-10-08T02:45:11Z","timestamp":1570502711000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11634-017-0305-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12,15]]},"references-count":36,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["305"],"URL":"https:\/\/doi.org\/10.1007\/s11634-017-0305-y","relation":{},"ISSN":["1862-5347","1862-5355"],"issn-type":[{"value":"1862-5347","type":"print"},{"value":"1862-5355","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12,15]]}}}