LEADER 02433nam0 2200445 i 450 001 VAN0113952 005 20230706102807.664 017 70$2N$a9783662483442 100 $a20180123d2015 |0itac50 ba 101 $aeng 102 $aDE 105 $a|||| ||||| 200 1 $aRankings and preferences$enew results in weighted correlation and weighted principal component analysis with applications$fJoaquim Pinto da Costa 210 $aBerlin$aHeidelberg$cSpringer$d2015 215 $aX, 91 p.$cill.$d24 cm 410 1$1001VAN0102916$12001 $aSpringerBriefs in statistics$1210 $aBerlin [etc.]$cSpringer$d2011- 500 1$3VAN0235218$aRankings and preferences : new results in weighted correlation and weighted principal component analysis with applications$92440601 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a62P10$xApplications of statistics to biology and medical sciences; meta analysis [MSC 2020]$3VANC024649$2MF 606 $a62M10$xTime series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020]$3VANC025079$2MF 606 $a62H25$xFactor analysis and principal components; correspondence analysis [MSC 2020]$3VANC025575$2MF 606 $a62H20$xMeasures of association (correlation, canonical correlation, etc.) [MSC 2020]$3VANC031434$2MF 606 $a62F07$xStatistical ranking and selection procedures [MSC 2020]$3VANC033732$2MF 610 $aMicroarray data$9KW:K 610 $aPrincipal component analysis$9KW:K 610 $aRanking$9KW:K 610 $aTime series$9KW:K 610 $aWeighted correlation$9KW:K 620 $dBerlin$3VANL000066 620 $aDE$dHeidelberg$3VANL000282 700 1$aPinto da Costa$bJoaquim$3VANV088040$0755704 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttp://dx.doi.org/10.1007/978-3-662-48344-2$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN0113952 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 0401 $e08eMF401 20180123 996 $aRankings and preferences : new results in weighted correlation and weighted principal component analysis with applications$92440601 997 $aUNICAMPANIA