Model-based clustering for multivariate functional data
The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, based on the assumption of normality of the principal component scores, is defined and estimated by an...
Saved in:
| Published in | Computational statistics & data analysis Vol. 71; pp. 92 - 106 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.03.2014
Elsevier |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, based on the assumption of normality of the principal component scores, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into account the dependence among curves. Results on simulated and real datasets show the efficiency of the proposed method. |
|---|---|
| AbstractList | The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, based on the assumption of normality of the principal component scores, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into account the dependence among curves. Results on simulated and real datasets show the efficiency of the proposed method. This paper proposes the first model-based clustering algorithm for multivariate functional data. After introducing multivariate functional principal components analysis (MFPCA), a parametric mixture model, {based on the assumption of normality of the principal components}, is defined and estimated by an EM-like algorithm. The main advantage of the proposed model is its ability to take into account the dependence among curves. Results on simulated and real datasets show the efficiency of the proposed method. |
| Author | Preda, Cristian Jacques, Julien |
| Author_xml | – sequence: 1 givenname: Julien surname: Jacques fullname: Jacques, Julien email: julien.jacques@polytech-lille.fr – sequence: 2 givenname: Cristian surname: Preda fullname: Preda, Cristian email: cristian.preda@polytech-lille.fr |
| BackLink | https://hal.science/hal-00713334$$DView record in HAL |
| BookMark | eNqFkEFr2zAUgEXpoEnXP9CTj9vB2ZNkWzbsEsLaDjJ26V3I0lOroFidJAf27yeTssMOGTx4IL5PPL41uZ7ChITcU9hQoN2Xw0YnozYMKNuUAWiuyIr2gtWCt-yarAok6qER_IasUzoAAGtEvyLiRzDo61ElNJX2c8oY3fRS2RCr4-yzO6noVMbKzpPOLkzKV0Zl9ZF8sMonvHvft-T54dvz7qne_3z8vtvua91SyHXPQYOlwnJDRWOwE8No234oR48URuhMO7bjMPLeWgQhOjECKGULqzUIfks-n799VV6-RXdU8bcMysmn7V4ubwCCcs6bEyvspzP7FsOvGVOWR5c0eq8mDHOSjLWc0YYN_X9R2kLHS72BF5SdUR1DShHt3zMoyKW9PMilvVzayzKlfZH6fyTtslry5aicv6x-PatYqp4cRpm0w0mjcRF1lia4S_ofX7yfmQ |
| CitedBy_id | crossref_primary_10_1007_s00180_020_00958_4 crossref_primary_10_1007_s00180_022_01236_1 crossref_primary_10_1007_s00180_016_0676_0 crossref_primary_10_1080_14763141_2017_1384050 crossref_primary_10_1111_ejn_15998 crossref_primary_10_1155_jpas_5074649 crossref_primary_10_1016_j_jmva_2019_104568 crossref_primary_10_1007_s41237_018_0066_8 crossref_primary_10_1016_j_jmva_2021_104874 crossref_primary_10_5604_01_3001_0014_1152 crossref_primary_10_1371_journal_pone_0311418 crossref_primary_10_1002_cjs_11803 crossref_primary_10_1007_s00477_017_1441_9 crossref_primary_10_1515_jtse_2019_0047 crossref_primary_10_5194_dwes_10_75_2017 crossref_primary_10_1016_j_csda_2016_06_007 crossref_primary_10_1016_j_procs_2018_03_035 crossref_primary_10_1214_17_AOS1553 crossref_primary_10_1007_s11760_015_0749_5 crossref_primary_10_1007_s10260_023_00719_9 crossref_primary_10_1016_j_ins_2024_120932 crossref_primary_10_3390_stats4010014 crossref_primary_10_1007_s00362_023_01467_4 crossref_primary_10_1080_00949655_2022_2053855 crossref_primary_10_1007_s11047_018_9720_z crossref_primary_10_1111_insr_12588 crossref_primary_10_1287_ijds_2022_0034 crossref_primary_10_1111_biom_13851 crossref_primary_10_1007_s11634_020_00432_5 crossref_primary_10_1007_s10203_023_00417_x crossref_primary_10_1080_03610918_2020_1764033 crossref_primary_10_1007_s10260_018_00446_6 crossref_primary_10_1007_s13253_021_00477_9 crossref_primary_10_1016_j_csda_2022_107496 crossref_primary_10_1016_j_humov_2014_03_008 crossref_primary_10_1080_10485252_2024_2358435 crossref_primary_10_1016_j_jmva_2020_104675 crossref_primary_10_1080_14763141_2024_2398508 crossref_primary_10_1080_10485252_2024_2396361 crossref_primary_10_1097_AJP_0000000000001041 crossref_primary_10_1177_09622802211002865 crossref_primary_10_1214_21_AOAS1514 crossref_primary_10_1145_3581789 crossref_primary_10_1142_S0218488520500087 crossref_primary_10_1007_s00357_016_9212_8 crossref_primary_10_1016_j_ins_2020_06_014 crossref_primary_10_1002_cjs_11680 crossref_primary_10_1111_jtsa_12675 crossref_primary_10_1002_widm_1298 crossref_primary_10_1002_cem_3394 crossref_primary_10_1080_10618600_2022_2149540 crossref_primary_10_1016_j_csda_2016_07_010 crossref_primary_10_1080_00224065_2018_1438007 crossref_primary_10_1007_s00477_024_02700_8 crossref_primary_10_1007_s00477_021_02071_4 crossref_primary_10_1016_j_pocean_2023_103120 crossref_primary_10_1007_s11634_023_00542_w crossref_primary_10_1007_s00357_020_09369_y crossref_primary_10_1007_s11336_023_09918_5 crossref_primary_10_1214_18_BJPS418 crossref_primary_10_1002_sta4_245 crossref_primary_10_5194_hess_24_3951_2020 crossref_primary_10_1007_s11634_017_0290_1 crossref_primary_10_21307_stattrans_2016_079 crossref_primary_10_1080_03610926_2019_1602650 crossref_primary_10_1080_00949655_2021_1903463 crossref_primary_10_5604_01_3001_0014_0897 crossref_primary_10_1002_sim_8794 crossref_primary_10_1214_15_AOAS861 crossref_primary_10_1146_annurev_statistics_041715_033624 crossref_primary_10_1016_j_csda_2021_107376 crossref_primary_10_1109_TR_2020_3035084 crossref_primary_10_1007_s11222_023_10379_0 crossref_primary_10_1007_s11222_022_10128_9 crossref_primary_10_21307_stattrans_2019_018 crossref_primary_10_1038_s41598_022_06767_7 crossref_primary_10_1007_s10489_020_01765_6 crossref_primary_10_1016_j_jmva_2021_104891 crossref_primary_10_1002_sim_9654 crossref_primary_10_3390_analytics2040041 crossref_primary_10_1007_s00500_019_04505_2 crossref_primary_10_1080_01621459_2016_1273115 crossref_primary_10_1007_s12561_024_09419_8 crossref_primary_10_1177_0962280220921912 crossref_primary_10_1007_s00357_025_09503_8 crossref_primary_10_1016_j_future_2020_05_018 crossref_primary_10_1016_j_heliyon_2024_e41251 crossref_primary_10_1007_s11222_023_10288_2 crossref_primary_10_1080_00401706_2018_1456976 crossref_primary_10_1515_bile_2016_0010 crossref_primary_10_1007_s10651_015_0317_8 crossref_primary_10_1109_ACCESS_2019_2926579 crossref_primary_10_1007_s12561_023_09399_1 crossref_primary_10_1007_s11135_022_01611_6 crossref_primary_10_1093_biomet_asae015 crossref_primary_10_1177_1094428117725793 crossref_primary_10_1111_rssc_12404 crossref_primary_10_1016_j_knosys_2018_01_035 crossref_primary_10_1080_03610918_2018_1494280 crossref_primary_10_1002_bimj_201500027 crossref_primary_10_1088_1755_1315_526_1_012029 crossref_primary_10_1109_ACCESS_2023_3322929 crossref_primary_10_1109_JSTARS_2023_3288521 crossref_primary_10_1093_jrsssc_qlad017 crossref_primary_10_1002_app_50705 crossref_primary_10_1111_rssb_12337 crossref_primary_10_21307_stattrans_2016_032 crossref_primary_10_1007_s41096_022_00122_9 crossref_primary_10_1214_22_AOAS1602 crossref_primary_10_1109_TFUZZ_2021_3050857 crossref_primary_10_1177_0962280218815301 crossref_primary_10_1002_env_2370 crossref_primary_10_1111_rssc_12310 crossref_primary_10_1111_biom_13340 crossref_primary_10_1214_24_AOAS1989 crossref_primary_10_1016_j_neucom_2018_02_055 crossref_primary_10_1080_02664763_2016_1247791 crossref_primary_10_1080_00224065_2023_2219012 crossref_primary_10_1007_s11634_022_00500_y crossref_primary_10_1007_s00357_020_09363_4 crossref_primary_10_1007_s13571_019_00221_x crossref_primary_10_1016_j_ins_2018_12_060 crossref_primary_10_5194_hess_27_673_2023 crossref_primary_10_1016_j_matcom_2024_04_017 crossref_primary_10_1016_j_ijar_2018_05_002 crossref_primary_10_1080_10586458_2024_2423866 crossref_primary_10_1002_bimj_202300363 crossref_primary_10_1007_s00362_015_0710_2 crossref_primary_10_21307_stattrans_2015_006 crossref_primary_10_1016_j_jmva_2018_09_002 crossref_primary_10_1016_j_csda_2016_01_019 crossref_primary_10_1007_s11634_013_0158_y crossref_primary_10_4018_IJHCITP_2018010101 crossref_primary_10_1016_j_spl_2019_04_017 crossref_primary_10_1109_TNNLS_2021_3137795 crossref_primary_10_22630_MIBE_2018_19_2_17 crossref_primary_10_1371_journal_pone_0310991 crossref_primary_10_1093_biostatistics_kxad013 crossref_primary_10_3150_17_BEJ929 crossref_primary_10_1016_j_ecosta_2023_03_002 crossref_primary_10_1080_03610918_2020_1830292 crossref_primary_10_1002_cjs_11838 crossref_primary_10_1016_j_jmva_2024_105355 crossref_primary_10_1016_j_csda_2020_107160 crossref_primary_10_1016_j_jspi_2014_05_008 crossref_primary_10_1016_j_jmva_2020_104662 crossref_primary_10_6339_21_JDS1031 crossref_primary_10_3390_su141912918 crossref_primary_10_1146_annurev_statistics_033121_115326 crossref_primary_10_1002_env_2437 crossref_primary_10_1016_j_patrec_2020_04_024 crossref_primary_10_1007_s11634_022_00501_x crossref_primary_10_1080_01621459_2021_1917416 crossref_primary_10_1214_21_AOAS1542 crossref_primary_10_1177_0962280214549040 crossref_primary_10_1016_j_jmva_2023_105243 crossref_primary_10_1146_annurev_statistics_032921_033726 crossref_primary_10_1093_jrsssc_qlad100 crossref_primary_10_1002_sim_9917 crossref_primary_10_1111_rssc_12563 crossref_primary_10_1214_23_AOAS1827 crossref_primary_10_1002_sim_9117 crossref_primary_10_1002_bimj_201900112 crossref_primary_10_3150_20_BEJ1246 crossref_primary_10_1002_sim_10151 crossref_primary_10_1002_sim_9353 crossref_primary_10_1177_1471082X211056158 crossref_primary_10_1007_s10109_021_00352_8 crossref_primary_10_1360_SSM_2021_0081 crossref_primary_10_1002_2017WR021650 crossref_primary_10_1002_sta4_435 crossref_primary_10_1002_sta4_557 crossref_primary_10_1007_s11749_020_00733_z crossref_primary_10_1002_cem_2560 crossref_primary_10_1007_s00180_018_0808_9 crossref_primary_10_1214_23_AOAS1857 crossref_primary_10_1080_10618600_2024_2304633 crossref_primary_10_1016_j_csda_2024_108069 crossref_primary_10_1007_s11205_020_02355_2 crossref_primary_10_1007_s11205_023_03098_6 crossref_primary_10_1186_s41118_018_0043_9 crossref_primary_10_1214_21_AOAS1547 crossref_primary_10_1016_j_ijar_2021_10_008 crossref_primary_10_1016_j_jspi_2023_106133 crossref_primary_10_1016_j_future_2023_12_021 crossref_primary_10_1007_s11634_023_00567_1 crossref_primary_10_3390_su11061620 crossref_primary_10_3390_joitmc8010006 crossref_primary_10_1016_j_jmva_2022_105095 crossref_primary_10_1111_rssc_12589 crossref_primary_10_1007_s00362_016_0757_8 crossref_primary_10_1016_j_csda_2013_10_010 crossref_primary_10_1016_j_chemolab_2015_09_018 |
| Cites_doi | 10.1007/s11634-011-0095-6 10.1007/s00180-006-0013-0 10.1111/j.1467-9868.2007.00605.x 10.1198/016214503000189 10.1198/073500107000000106 10.1007/s00180-007-0041-4 10.1111/1467-9469.00350 10.1016/j.neucom.2012.11.042 10.1214/09-AOS741 10.1016/j.csda.2009.12.008 10.1111/j.1467-9868.2006.00545.x 10.1111/j.2517-6161.1977.tb01600.x 10.1016/j.csda.2011.03.011 10.1207/s15327906mbr0102_10 10.1214/aos/1176344136 10.1023/B:STCO.0000035306.77434.31 10.1002/cem.945 10.1007/s00357-003-0007-3 10.1016/S0167-9473(03)00032-X 10.1016/j.jspi.2006.06.011 10.1016/j.csda.2008.11.019 10.1007/s00357-010-9054-8 10.1016/j.csda.2011.03.018 10.1016/j.csda.2007.02.009 |
| ContentType | Journal Article |
| Copyright | 2012 Elsevier B.V. Distributed under a Creative Commons Attribution 4.0 International License |
| Copyright_xml | – notice: 2012 Elsevier B.V. – notice: Distributed under a Creative Commons Attribution 4.0 International License |
| DBID | AAYXX CITATION 7SC 8FD JQ2 L7M L~C L~D 7S9 L.6 1XC VOOES |
| DOI | 10.1016/j.csda.2012.12.004 |
| DatabaseName | CrossRef Computer and Information Systems Abstracts Technology Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional AGRICOLA AGRICOLA - Academic Hyper Article en Ligne (HAL) Hyper Article en Ligne (HAL) (Open Access) |
| DatabaseTitle | CrossRef Computer and Information Systems Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | Computer and Information Systems Abstracts AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Mathematics Statistics |
| EISSN | 1872-7352 |
| EndPage | 106 |
| ExternalDocumentID | oai_HAL_hal_00713334v2 10_1016_j_csda_2012_12_004 S0167947312004380 |
| GroupedDBID | --K --M -~X .~1 0R~ 1B1 1OL 1RT 1~. 1~5 29F 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN 9JO AAAKF AAAKG AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARIN AAXUO AAYFN ABAOU ABBOA ABFNM ABMAC ABTAH ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADGUI ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AI. AIALX AIEXJ AIGVJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HAMUX HLZ HMJ HVGLF HZ~ H~9 IHE J1W JJJVA KOM LG9 LY1 M26 M41 MHUIS MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SBC SDF SDG SDS SES SEW SME SPC SPCBC SSB SSD SST SSV SSW SSZ T5K VH1 VOH WUQ XPP ZMT ZY4 ~02 ~G- AAHBH AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACRPL ACVFH ADCNI ADNMO ADXHL AEIPS AEUPX AFJKZ AFPUW AFXIZ AGCQF AGQPQ AGRNS AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP BNPGV CITATION SSH 7SC 8FD EFKBS JQ2 L7M L~C L~D 7S9 L.6 1XC UMC VOOES |
| ID | FETCH-LOGICAL-c510t-830c0f17f3d174de679bf589101b10b06d5b5b9b38ffe07767b00aaf74dcc073 |
| IEDL.DBID | .~1 |
| ISSN | 0167-9473 |
| IngestDate | Fri May 09 12:24:08 EDT 2025 Thu Jul 10 18:31:44 EDT 2025 Mon Jul 21 09:44:04 EDT 2025 Tue Jul 01 02:24:27 EDT 2025 Thu Apr 24 23:03:21 EDT 2025 Fri Feb 23 02:23:51 EST 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Multivariate functional principal component analysis Multivariate functional data Density approximation EM-algorithm Model-based clustering multivariate functional principal component analysis model-based clustering EM algorithm density approximation |
| Language | English |
| License | Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c510t-830c0f17f3d174de679bf589101b10b06d5b5b9b38ffe07767b00aaf74dcc073 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
| ORCID | 0000-0003-4808-2781 0000-0003-1250-177X |
| OpenAccessLink | https://hal.science/hal-00713334 |
| PQID | 1506387293 |
| PQPubID | 23500 |
| PageCount | 15 |
| ParticipantIDs | hal_primary_oai_HAL_hal_00713334v2 proquest_miscellaneous_2253214298 proquest_miscellaneous_1506387293 crossref_primary_10_1016_j_csda_2012_12_004 crossref_citationtrail_10_1016_j_csda_2012_12_004 elsevier_sciencedirect_doi_10_1016_j_csda_2012_12_004 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2014-03-01 |
| PublicationDateYYYYMMDD | 2014-03-01 |
| PublicationDate_xml | – month: 03 year: 2014 text: 2014-03-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | Computational statistics & data analysis |
| PublicationYear | 2014 |
| Publisher | Elsevier B.V Elsevier |
| Publisher_xml | – name: Elsevier B.V – name: Elsevier |
| References | Berrendero, Justel, Svarc (br000010) 2011; 55 Schwarz (br000160) 1978; 6 Tuddenham, R., Snyder, M., 1954. Physical growth of California boys and girls from birth to eighteen years. Universities of California Public Child Development 1, pp. 188–364. Sangalli, Secchi, Vantini, Vitelli (br000150) 2010; 54 Abraham, Cornillon, Matzner-Løber, Molinari (br000005) 2003; 30 Cattell (br000035) 1966; 1 Chiou, Li (br000040) 2007; 69 McLachlan, Peel (br000110) 2000 Saporta (br000155) 1981; vols. 37–38 Singhal, Seborg (br000165) 2005; 19 Preda, Saporta, Lévéder (br000130) 2007; 22 Besse, P., 1979. Etude descriptive d’un processus. Ph.D. Thesis. Université Paul Sabatier, Toulouse. Bouveyron, Girard, Schmid (br000025) 2007; 52 Biernacki (br000020) 2004; 14 Ray, Mallick (br000140) 2006; 68 Jacques, J., Preda, C., 2013. Funclust: a curves clustering method using functional random variable density approximation. Neurocomputing (in press). Ramsay, Silverman (br000135) 2005 Bouveyron, Jacques (br000030) 2011; 5 Ferraty, Vieu (br000060) 2003; 44 Frühwirth-Schnatter, Kaufmann (br000065) 2008; 26 Olszewski, R., 2001. Generalized feature extraction for structural pattern recognition in time-series data. Ph.D. Thesis. Carnegie Mellon University. Pittsburgh, PA. Leveder, C., Abraham, C., Cornillon, P.A., Matzner-Løber, E., Molinari, N., 2004. Discrimination de courbes de pétrissage. In: Chimiométrie 2004. Paris. pp. 37–43. James, Sugar (br000090) 2003; 98 Titterington, Smith, Makov (br000175) 1985 Dempster, Laird, Rubin (br000050) 1977; 39 Liu, Yang (br000105) 2009; 53 R Core Team, 2012. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. . Kayano, Dozono, Konishi (br000095) 2010; 27 Poskitt, Sengarapillai (br000120) 2013; 58 Guyon, I., Von Luxburg, U., Williamson, R., 2009. Clustering: science or art. In: NIPS 2009 Workshop on Clustering Theory. Tarpey, Kinateder (br000170) 2003; 20 Tokushige, Yadohisa, Inada (br000180) 2007; 22 Deville (br000055) 1974; 15 Preda (br000125) 2007; 137 Ieva, Paganoni, Pigoli, Vitelli (br000075) 2012 Jacques, J., Preda, C., 2012. Model-based clustering of functional data. In: 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges. pp. 459–464. Delaigle, Hall (br000045) 2010; 38 Dempster (10.1016/j.csda.2012.12.004_br000050) 1977; 39 Preda (10.1016/j.csda.2012.12.004_br000130) 2007; 22 Liu (10.1016/j.csda.2012.12.004_br000105) 2009; 53 10.1016/j.csda.2012.12.004_br000015 10.1016/j.csda.2012.12.004_br000115 James (10.1016/j.csda.2012.12.004_br000090) 2003; 98 Tokushige (10.1016/j.csda.2012.12.004_br000180) 2007; 22 McLachlan (10.1016/j.csda.2012.12.004_br000110) 2000 Titterington (10.1016/j.csda.2012.12.004_br000175) 1985 Biernacki (10.1016/j.csda.2012.12.004_br000020) 2004; 14 Bouveyron (10.1016/j.csda.2012.12.004_br000025) 2007; 52 10.1016/j.csda.2012.12.004_br000070 Ieva (10.1016/j.csda.2012.12.004_br000075) 2012 Ramsay (10.1016/j.csda.2012.12.004_br000135) 2005 Sangalli (10.1016/j.csda.2012.12.004_br000150) 2010; 54 Poskitt (10.1016/j.csda.2012.12.004_br000120) 2013; 58 10.1016/j.csda.2012.12.004_br000145 10.1016/j.csda.2012.12.004_br000185 10.1016/j.csda.2012.12.004_br000100 10.1016/j.csda.2012.12.004_br000085 Ferraty (10.1016/j.csda.2012.12.004_br000060) 2003; 44 Preda (10.1016/j.csda.2012.12.004_br000125) 2007; 137 10.1016/j.csda.2012.12.004_br000080 Singhal (10.1016/j.csda.2012.12.004_br000165) 2005; 19 Bouveyron (10.1016/j.csda.2012.12.004_br000030) 2011; 5 Delaigle (10.1016/j.csda.2012.12.004_br000045) 2010; 38 Saporta (10.1016/j.csda.2012.12.004_br000155) 1981; vols. 37–38 Cattell (10.1016/j.csda.2012.12.004_br000035) 1966; 1 Berrendero (10.1016/j.csda.2012.12.004_br000010) 2011; 55 Frühwirth-Schnatter (10.1016/j.csda.2012.12.004_br000065) 2008; 26 Ray (10.1016/j.csda.2012.12.004_br000140) 2006; 68 Schwarz (10.1016/j.csda.2012.12.004_br000160) 1978; 6 Chiou (10.1016/j.csda.2012.12.004_br000040) 2007; 69 Deville (10.1016/j.csda.2012.12.004_br000055) 1974; 15 Abraham (10.1016/j.csda.2012.12.004_br000005) 2003; 30 Kayano (10.1016/j.csda.2012.12.004_br000095) 2010; 27 Tarpey (10.1016/j.csda.2012.12.004_br000170) 2003; 20 |
| References_xml | – volume: 39 start-page: 1 year: 1977 end-page: 38 ident: br000050 article-title: Maximum likelihood from incomplete data via the EM algorithm publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology – volume: 68 start-page: 305 year: 2006 end-page: 332 ident: br000140 article-title: Functional clustering by Bayesian wavelet methods publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology – volume: 53 start-page: 1361 year: 2009 end-page: 1376 ident: br000105 article-title: Simultaneous curve registration and clustering for functional data publication-title: Computational Statistics and Data Analysis – volume: 137 start-page: 829 year: 2007 end-page: 840 ident: br000125 article-title: Regression models for functional data by reproducing kernel Hilbert spaces methods publication-title: Journal of Statistical Planning and Inference – volume: 55 start-page: 2619 year: 2011 end-page: 2634 ident: br000010 article-title: Principal components for multivariate functional data publication-title: Computational Statistics and Data Analysis – volume: 52 start-page: 502 year: 2007 end-page: 519 ident: br000025 article-title: High dimensional data clustering publication-title: Computational Statistics and Data Analysis – reference: Jacques, J., Preda, C., 2012. Model-based clustering of functional data. In: 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges. pp. 459–464. – reference: Besse, P., 1979. Etude descriptive d’un processus. Ph.D. Thesis. Université Paul Sabatier, Toulouse. – volume: 15 start-page: 3 year: 1974 end-page: 101 ident: br000055 article-title: Méthodes statistiques et numériques de l’analyse harmonique publication-title: Annales de l’INSEE – volume: 26 start-page: 78 year: 2008 end-page: 89 ident: br000065 article-title: Model-based clustering of multiple time series publication-title: Journal of Business and Economic Statistics – volume: 98 start-page: 397 year: 2003 end-page: 408 ident: br000090 article-title: Clustering for sparsely sampled functional data publication-title: Journal of the American Statistical Association – year: 2000 ident: br000110 article-title: Finite Mixture Models – year: 2005 ident: br000135 publication-title: Functional Data Analysis – reference: Tuddenham, R., Snyder, M., 1954. Physical growth of California boys and girls from birth to eighteen years. Universities of California Public Child Development 1, pp. 188–364. – volume: 20 start-page: 93 year: 2003 end-page: 114 ident: br000170 article-title: Clustering functional data publication-title: Journal of Classification – year: 1985 ident: br000175 publication-title: Statistical Analysis of Finite Mixture Distributions – reference: R Core Team, 2012. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. – volume: 22 start-page: 1 year: 2007 end-page: 16 ident: br000180 article-title: Crisp and fuzzy publication-title: Computational Statistics – volume: 27 start-page: 211 year: 2010 end-page: 230 ident: br000095 article-title: Functional cluster analysis via orthonormalized Gaussian basis expansions and its application publication-title: Journal of Classification – volume: 19 start-page: 427 year: 2005 end-page: 438 ident: br000165 article-title: Clustering multivariate time-series data publication-title: Journal of Chemometrics – volume: 14 start-page: 267 year: 2004 end-page: 279 ident: br000020 article-title: Initializing EM using the properties of its trajectories in Gaussian mixtures publication-title: Statistics and Computing – volume: vols. 37–38 year: 1981 ident: br000155 publication-title: Méthodes Exploratoires d’Analyse de Données Temporelles – volume: 30 start-page: 581 year: 2003 end-page: 595 ident: br000005 article-title: Unsupervised curve clustering using publication-title: Scandinavian Journal of Statistics. Theory and Applications – volume: 58 start-page: 98 year: 2013 end-page: 113 ident: br000120 article-title: Description length and dimensionality reduction in functional data analysis publication-title: Computational Statistics and Data Analysis – volume: 38 start-page: 1171 year: 2010 end-page: 1193 ident: br000045 article-title: Defining probability density for a distribution of random functions publication-title: The Annals of Statistics – volume: 5 start-page: 281 year: 2011 end-page: 300 ident: br000030 article-title: Model-based clustering of time series in group-specific functional subspaces publication-title: Advances in Data Analysis and Classification – reference: . – volume: 69 start-page: 679 year: 2007 end-page: 699 ident: br000040 article-title: Functional clustering and identifying substructures of longitudinal data publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology – reference: Leveder, C., Abraham, C., Cornillon, P.A., Matzner-Løber, E., Molinari, N., 2004. Discrimination de courbes de pétrissage. In: Chimiométrie 2004. Paris. pp. 37–43. – year: 2012 ident: br000075 article-title: Multivariate functional clustering for the morphological analysis of electrocardiograph curves publication-title: Journal of the Royal Statistical Society: Series C (Applied Statistics) – volume: 44 start-page: 161 year: 2003 end-page: 173 ident: br000060 article-title: Curves discrimination: a nonparametric approach publication-title: Computational Statistics and Data Analysis – volume: 54 start-page: 1219 year: 2010 end-page: 1233 ident: br000150 article-title: -means alignment for curve clustering publication-title: Computational Statistics and Data Analysis – reference: Jacques, J., Preda, C., 2013. Funclust: a curves clustering method using functional random variable density approximation. Neurocomputing (in press). – volume: 22 start-page: 223 year: 2007 end-page: 235 ident: br000130 article-title: PLS classification of functional data publication-title: Computational Statistics – volume: 6 start-page: 461 year: 1978 end-page: 464 ident: br000160 article-title: Estimating the dimension of a model publication-title: The Annals of Statistics – volume: 1 start-page: 245 year: 1966 end-page: 276 ident: br000035 article-title: The scree test for the number of factors publication-title: Multivariate Behavioral Research – reference: Guyon, I., Von Luxburg, U., Williamson, R., 2009. Clustering: science or art. In: NIPS 2009 Workshop on Clustering Theory. – reference: Olszewski, R., 2001. Generalized feature extraction for structural pattern recognition in time-series data. Ph.D. Thesis. Carnegie Mellon University. Pittsburgh, PA. – volume: 5 start-page: 281 issue: 4 year: 2011 ident: 10.1016/j.csda.2012.12.004_br000030 article-title: Model-based clustering of time series in group-specific functional subspaces publication-title: Advances in Data Analysis and Classification doi: 10.1007/s11634-011-0095-6 – volume: 22 start-page: 1 year: 2007 ident: 10.1016/j.csda.2012.12.004_br000180 article-title: Crisp and fuzzy k-means clustering algorithms for multivariate functional data publication-title: Computational Statistics doi: 10.1007/s00180-006-0013-0 – year: 1985 ident: 10.1016/j.csda.2012.12.004_br000175 – ident: 10.1016/j.csda.2012.12.004_br000080 – volume: 69 start-page: 679 issue: 4 year: 2007 ident: 10.1016/j.csda.2012.12.004_br000040 article-title: Functional clustering and identifying substructures of longitudinal data publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology doi: 10.1111/j.1467-9868.2007.00605.x – volume: 98 start-page: 397 issue: 462 year: 2003 ident: 10.1016/j.csda.2012.12.004_br000090 article-title: Clustering for sparsely sampled functional data publication-title: Journal of the American Statistical Association doi: 10.1198/016214503000189 – year: 2000 ident: 10.1016/j.csda.2012.12.004_br000110 – volume: 26 start-page: 78 year: 2008 ident: 10.1016/j.csda.2012.12.004_br000065 article-title: Model-based clustering of multiple time series publication-title: Journal of Business and Economic Statistics doi: 10.1198/073500107000000106 – volume: 22 start-page: 223 issue: 2 year: 2007 ident: 10.1016/j.csda.2012.12.004_br000130 article-title: PLS classification of functional data publication-title: Computational Statistics doi: 10.1007/s00180-007-0041-4 – ident: 10.1016/j.csda.2012.12.004_br000100 – volume: 30 start-page: 581 issue: 3 year: 2003 ident: 10.1016/j.csda.2012.12.004_br000005 article-title: Unsupervised curve clustering using B-splines publication-title: Scandinavian Journal of Statistics. Theory and Applications doi: 10.1111/1467-9469.00350 – ident: 10.1016/j.csda.2012.12.004_br000085 doi: 10.1016/j.neucom.2012.11.042 – volume: 38 start-page: 1171 year: 2010 ident: 10.1016/j.csda.2012.12.004_br000045 article-title: Defining probability density for a distribution of random functions publication-title: The Annals of Statistics doi: 10.1214/09-AOS741 – volume: 54 start-page: 1219 issue: 5 year: 2010 ident: 10.1016/j.csda.2012.12.004_br000150 article-title: K-means alignment for curve clustering publication-title: Computational Statistics and Data Analysis doi: 10.1016/j.csda.2009.12.008 – volume: 68 start-page: 305 issue: 2 year: 2006 ident: 10.1016/j.csda.2012.12.004_br000140 article-title: Functional clustering by Bayesian wavelet methods publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology doi: 10.1111/j.1467-9868.2006.00545.x – volume: 15 start-page: 3 year: 1974 ident: 10.1016/j.csda.2012.12.004_br000055 article-title: Méthodes statistiques et numériques de l’analyse harmonique publication-title: Annales de l’INSEE – year: 2005 ident: 10.1016/j.csda.2012.12.004_br000135 – volume: 39 start-page: 1 issue: 1 year: 1977 ident: 10.1016/j.csda.2012.12.004_br000050 article-title: Maximum likelihood from incomplete data via the EM algorithm publication-title: Journal of the Royal Statistical Society. Series B. Statistical Methodology doi: 10.1111/j.2517-6161.1977.tb01600.x – ident: 10.1016/j.csda.2012.12.004_br000115 – volume: 55 start-page: 2619 year: 2011 ident: 10.1016/j.csda.2012.12.004_br000010 article-title: Principal components for multivariate functional data publication-title: Computational Statistics and Data Analysis doi: 10.1016/j.csda.2011.03.011 – volume: 1 start-page: 245 issue: 2 year: 1966 ident: 10.1016/j.csda.2012.12.004_br000035 article-title: The scree test for the number of factors publication-title: Multivariate Behavioral Research doi: 10.1207/s15327906mbr0102_10 – volume: 6 start-page: 461 issue: 2 year: 1978 ident: 10.1016/j.csda.2012.12.004_br000160 article-title: Estimating the dimension of a model publication-title: The Annals of Statistics doi: 10.1214/aos/1176344136 – volume: 14 start-page: 267 issue: 3 year: 2004 ident: 10.1016/j.csda.2012.12.004_br000020 article-title: Initializing EM using the properties of its trajectories in Gaussian mixtures publication-title: Statistics and Computing doi: 10.1023/B:STCO.0000035306.77434.31 – ident: 10.1016/j.csda.2012.12.004_br000145 – volume: vols. 37–38 year: 1981 ident: 10.1016/j.csda.2012.12.004_br000155 – volume: 19 start-page: 427 year: 2005 ident: 10.1016/j.csda.2012.12.004_br000165 article-title: Clustering multivariate time-series data publication-title: Journal of Chemometrics doi: 10.1002/cem.945 – volume: 20 start-page: 93 issue: 1 year: 2003 ident: 10.1016/j.csda.2012.12.004_br000170 article-title: Clustering functional data publication-title: Journal of Classification doi: 10.1007/s00357-003-0007-3 – year: 2012 ident: 10.1016/j.csda.2012.12.004_br000075 article-title: Multivariate functional clustering for the morphological analysis of electrocardiograph curves publication-title: Journal of the Royal Statistical Society: Series C (Applied Statistics) – volume: 44 start-page: 161 year: 2003 ident: 10.1016/j.csda.2012.12.004_br000060 article-title: Curves discrimination: a nonparametric approach publication-title: Computational Statistics and Data Analysis doi: 10.1016/S0167-9473(03)00032-X – volume: 137 start-page: 829 year: 2007 ident: 10.1016/j.csda.2012.12.004_br000125 article-title: Regression models for functional data by reproducing kernel Hilbert spaces methods publication-title: Journal of Statistical Planning and Inference doi: 10.1016/j.jspi.2006.06.011 – volume: 53 start-page: 1361 year: 2009 ident: 10.1016/j.csda.2012.12.004_br000105 article-title: Simultaneous curve registration and clustering for functional data publication-title: Computational Statistics and Data Analysis doi: 10.1016/j.csda.2008.11.019 – ident: 10.1016/j.csda.2012.12.004_br000185 – volume: 27 start-page: 211 year: 2010 ident: 10.1016/j.csda.2012.12.004_br000095 article-title: Functional cluster analysis via orthonormalized Gaussian basis expansions and its application publication-title: Journal of Classification doi: 10.1007/s00357-010-9054-8 – volume: 58 start-page: 98 year: 2013 ident: 10.1016/j.csda.2012.12.004_br000120 article-title: Description length and dimensionality reduction in functional data analysis publication-title: Computational Statistics and Data Analysis doi: 10.1016/j.csda.2011.03.018 – ident: 10.1016/j.csda.2012.12.004_br000015 – volume: 52 start-page: 502 year: 2007 ident: 10.1016/j.csda.2012.12.004_br000025 article-title: High dimensional data clustering publication-title: Computational Statistics and Data Analysis doi: 10.1016/j.csda.2007.02.009 – ident: 10.1016/j.csda.2012.12.004_br000070 |
| SSID | ssj0002478 |
| Score | 2.5253878 |
| Snippet | The first model-based clustering algorithm for multivariate functional data is proposed. After introducing multivariate functional principal components... This paper proposes the first model-based clustering algorithm for multivariate functional data. After introducing multivariate functional principal components... |
| SourceID | hal proquest crossref elsevier |
| SourceType | Open Access Repository Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 92 |
| SubjectTerms | Algorithms data collection Density approximation EM-algorithm Mathematics Model-based clustering Multivariate functional data Multivariate functional principal component analysis principal component analysis Statistics Statistics Theory |
| Title | Model-based clustering for multivariate functional data |
| URI | https://dx.doi.org/10.1016/j.csda.2012.12.004 https://www.proquest.com/docview/1506387293 https://www.proquest.com/docview/2253214298 https://hal.science/hal-00713334 |
| Volume | 71 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NS8MwFA9zXvQgfuL8GFW8SV3bJGtzHMNRndtBJ-4WmrTFyeiG-zj6t_te004U3UEolIaUhpfkfaS_93uEXDGmtQ9Rlw1hV9NmNHVtEXmBnfCYRR6LwKHD5ORevxk-s_shH1ZIu8yFQVhlofuNTs-1ddHSKKTZmI5GjScE0AvmU9czvOmYwc58XOU3H18wD48ZbYz83ti7SJwxGC89i5F7yPXyI8GiWNsvxmnjFVGSP5R1boE6u2SncB2tlhndHqkk2T7Z7q14V2cHxMfSZmMbTVNs6fECWRDANlngmVo5dHAJoTF4lxaaM3MKaCFG9JAMOreDdmgXpRFsDZtobgfU0U7q-imNIaSIE5CESrFAoOMq11FOM-aKK6FokKZJztgD2yuKUuirNezqI1LNJllyTCxFUyE49yPMkFWUCk6dONbUTbgW2lE14pYikbqgDcfqFWNZ4sPeJIpRohglXCDGGrlevTM1pBlre_NS0vLb1EvQ6mvfu4RpWX0AebLD1oPENhN7U7b0auSinDUJGwf_hkRZMlnMJFIr0gBiC_p3H1B2WMjJE8HJPwd5SrbgiRnU2hmpzt8XyTm4MXNVz9dpnWy27rphH-_dx5fuJzOZ8C4 |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3NT9swFH_i47DtMA3GRPdFQNtpCk380SSHHdAGamnLZZ3UmxU7jgBVAS0t0y77o_gLeS92ijZtPSAh5eTYjvVsvw_n598D-CCEMQlGXSGGXb1Q8DIOs5yloZWFyJnI0aGjy8njs17_uzidyuka3LZ3YQhW6XW_0-mNtvYlXS_N7vXFRfcbAegzkfCYOd50j6wc2l8_MW6rPw--4iR_ZOzkePKlH_rUAqHBRTgPUx6ZqIyTkhfokhcWe9IlJdiLYh1HOuoVUkudaZ6WpW0Yb3B55nmJdY3BXYHdrsOmQG1BWRMOf9_DSphw2p_4xGl0_qKOw5SZuiCuo5g1R5A-Odw_jOH6OaEy_zIOjcU7eQHPvasaHDlpbMGarbbh2XjJ81q_hIRSqc1CMoVFYGYLYl1AWxigJxw0UMUbDMXRmw3IfLpTx4AwqTsweQx5vYKN6qqyuxBoXmaZlElON3I155nkUVEYHltpMhPpDsStSJTxNOWULWOmWjzapSIxKhKjwgfF2IFPyzbXjqRjZW3ZSlr9sdQUWpGV7Q5wWpYfIF7u_tFIUZmL9bm4YR3Yb2dN4Ualvy95Za8WtSIqR55iLMP_XweVKyWOYln6-oGD3IMn_cl4pEaDs-EbeIpvhEPMvYWN-Y-FfYcu1Fy_b9ZsAOqR98gdN3speg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Model-based+clustering+for+multivariate+functional+data&rft.jtitle=Computational+statistics+%26+data+analysis&rft.au=Jacques%2C+Julien&rft.au=Preda%2C+Cristian&rft.date=2014-03-01&rft.issn=0167-9473&rft.volume=71&rft.spage=92&rft.epage=106&rft_id=info:doi/10.1016%2Fj.csda.2012.12.004&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_csda_2012_12_004 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0167-9473&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0167-9473&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0167-9473&client=summon |