LEADER 02218nam0 2200469 i 450 001 VAN00123391 005 20240806100813.447 017 70$2N$a9783319646718 100 $a20190919d2017 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aAlgorithms and programs of dynamic mixture estimation$eunified approach to different types of components$fIvan Nagy, Evgenia Suzdaleva 210 $aCham$cSpringer$d2017 215 $aXI, 113 p.$cill.$d24 cm 410 1$1001VAN00102916$12001 $aSpringerBriefs in statistics$1210 $aBerlin [etc.]$cSpringer$d2011- 500 1$3VAN00235383$aAlgorithms and programs of dynamic mixture estimation$91560462 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a62F10$xPoint estimation [MSC 2020]$3VANC021207$2MF 606 $a62F15$xBayesian inference [MSC 2020]$3VANC024528$2MF 606 $a62H12$xEstimation in multivariate analysis [MSC 2020]$3VANC021210$2MF 606 $a62H30$xClassification and discrimination; cluster analysis (statistical aspects) [MSC 2020]$3VANC028931$2MF 610 $aDynamic mixtures$9KW:K 610 $aMarkov switching models$9KW:K 610 $aMixture estimation algorithms$9KW:K 610 $aMixture models$9KW:K 610 $aMixture prediction$9KW:K 610 $aMixtures of various distributions$9KW:K 610 $aOpen source programs$9KW:K 610 $aRecursive Bayesian estimation$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aNagy$bIvan$3VANV094795$0766766 701 1$aSuzdaleva$bEvgenia$3VANV094796$0766767 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20241115$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-319-64671-8$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 $aVAN00123391 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08DLOAD e-book 0548 $e08eMF548 20190919 996 $aAlgorithms and programs of dynamic mixture Estimation$91560462 997 $aUNICAMPANIA