LEADER 04234nam 22006135 450 001 9910438032703321 005 20200707030006.0 010 $a1-4614-8283-6 024 7 $a10.1007/978-1-4614-8283-3 035 $a(CKB)3710000000024287 035 $a(EBL)1538864 035 $a(OCoLC)863203540 035 $a(SSID)ssj0001049555 035 $a(PQKBManifestationID)11588422 035 $a(PQKBTitleCode)TC0001049555 035 $a(PQKBWorkID)11018716 035 $a(PQKB)10131641 035 $a(DE-He213)978-1-4614-8283-3 035 $a(MiAaPQ)EBC1538864 035 $a(PPN)176098550 035 $a(EXLCZ)993710000000024287 100 $a20131017d2013 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aNew Perspectives in Partial Least Squares and Related Methods /$fedited by Herve Abdi, Wynne W. Chin, Vincenzo Esposito Vinzi, Giorgio Russolillo, Laura Trinchera 205 $a1st ed. 2013. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2013. 215 $a1 online resource (351 p.) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v56 300 $aDescription based upon print version of record. 311 $a1-4614-8282-8 320 $aIncludes bibliographical references and index. 327 $aKeynotes -- Large Datasets and Genomics -- Brain Imaging -- Multiblock Data Modeling. 330 $aNew Perspectives in Partial Least Squares and Related Methods shares original, peer-reviewed research from presentations during the 2012 partial least squares methods meeting (PLS 2012). This was the 7th meeting in the series of PLS conferences and the first to take place in the USA. PLS is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume, which include three invited contributions from our keynote speakers, provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. Prominent scientists from around the world took part in PLS 2012 and their contributions covered the multiple dimensions of the partial least squares-based methods. These exciting theoretical developments ranged from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. In following the tradition of the six previous PLS meetings, these contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy. Such a broad and comprehensive volume will also encourage new uses of PLS models in work by researchers and students in many fields. 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1009 ;$v56 606 $aStatistics  606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/S0000X 615 0$aStatistics . 615 14$aStatistical Theory and Methods. 615 24$aStatistics, general. 676 $a519.5 702 $aAbdi$b Herve$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aChin$b Wynne W$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aEsposito Vinzi$b Vincenzo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRussolillo$b Giorgio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTrinchera$b Laura$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910438032703321 996 $aNew perspectives in partial least squares and related methods$91495973 997 $aUNINA