LEADER 01190nam2 2200277 i 450 001 SUN0069766 005 20140625100049.660 020 $aIT$b884949 100 $a20090504d1986 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 200 1 $aˆ2: ‰1958-1978$fUgo La Malfa 210 $aRoma$cCamera dei deputati$d1986 215 $aXVI, P. 686-1410$d25 cm. 461 1$1001SUN0069762$12001 $aDiscorsi parlamentari$fUgo La Malfa$g[a cura di Massimo Scioscioli]$v2$1210 $aRoma$cCamera dei deputati$d1986$1215 $a2 v.$d25 cm. 606 $aDiritto pubblico e costituzionale italiano e comparato$2SG$3SUNC029468 620 $dRoma$3SUNL000360 700 1$aLa Malfa$b, Ugo$3SUNV054984$033106 712 $aCamera dei deputati$3SUNV000622$4650 801 $aIT$bSOL$c20181109$gRICA 912 $aSUN0069766 950 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI SCIENZE POLITICHE JEAN MONNET$d04 CONS 6D.1.2 $e04 OM 784 995 $aUFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI SCIENZE POLITICHE JEAN MONNET$gOM$h784$kCONS 6D.1.2$oc$qa 996 $a1958-1978$91436203 997 $aUNICAMPANIA LEADER 03537nam 2201021z- 450 001 9910637784003321 005 20221206 010 $a3-0365-5550-1 035 $a(CKB)5470000001631697 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/94553 035 $a(oapen)doab94553 035 $a(oapen)94553 035 $a(EXLCZ)995470000001631697 100 $a20202212d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data Analytics and Information Science for Business and Biomedical Applications II 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (196 p.) 311 08$a3-0365-5549-8 330 $aThe analysis of big data in biomedical, business and financial research has drawn much attention from researchers worldwide. This collection of articles aims to provide a platform for an in-depth discussion of novel statistical methods developed for the analysis of Big Data in these areas. Both applied and theoretical contributions to these areas are showcased. 606 $aComputer science$2bicssc 606 $aInformation technology industries$2bicssc 610 $aasymptotic bias and risk 610 $abandwidth selection 610 $aBayesian modeling 610 $abig data adaptation 610 $abrain network 610 $acancer 610 $acausal structure learning 610 $achest X-ray images 610 $aconsistency 610 $acorrelation 610 $adeep learning 610 $adividend estimation 610 $aedge-preserving image denoising 610 $aFCI algorithm 610 $afMRI 610 $afunctional connectivity 610 $afunctional predictor 610 $afunctional principal component analysis 610 $afunctional regression 610 $agestational weight 610 $ahigh dimensionality 610 $ahigh-dimensional data 610 $aHuman Connectome Project 610 $aimage sequence 610 $ainfant birth weight 610 $ajoint modeling 610 $ajump regression analysis 610 $aLASSO estimation 610 $alinear mixed model 610 $alinear mixed-effects model 610 $alocal smoothing 610 $alongitudinal data 610 $alung diseases 610 $amaternal weight gain 610 $amobile device 610 $amulticollinearity 610 $anetwork analysis 610 $anonparametric regression 610 $anonparametric testing 610 $aonline health community 610 $aoptions markets 610 $aPC algorithm 610 $apretest and shrinkage estimation 610 $apretrained neural networks 610 $aridge estimation 610 $asocial support 610 $asparse group regularization 610 $aspatio-temporal data 610 $astatistics 610 $atransfer learning 610 $awearable device data 610 $aweighted least squares 615 7$aComputer science 615 7$aInformation technology industries 700 $aAhmed$b S. Ejaz$4edt$01062202 702 $aNathoo$b Farouk$4edt 702 $aAhmed$b S. Ejaz$4oth 702 $aNathoo$b Farouk$4oth 906 $aBOOK 912 $a9910637784003321 996 $aBig Data Analytics and Information Science for Business and Biomedical Applications II$93024067 997 $aUNINA