LEADER 02442nam0 22004933i 450 001 VAN0274816 005 20240605035932.712 017 70$2N$a9783030800659 100 $a20240412d2021 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aHigh-Dimensional Covariance Matrix Estimation$eAn Introduction to Random Matrix Theory$fAygul Zagidullina 210 $aCham$cSpringer$d2021 215 $axiv, 115 p.$cill.$d24 cm 410 1$1001VAN0274817$12001 $aSpringerBriefs in Applied Statistics and Econometrics$1210 $aBerlin [etc.]$cSpringer 606 $a60-XX$xProbability theory and stochastic processes [MSC 2020]$3VANC020428$2MF 606 $a62H12$xEstimation in multivariate analysis [MSC 2020]$3VANC021210$2MF 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a62P20$xApplications of statistics to economics [MSC 2020]$3VANC026444$2MF 606 $a62R07$xStatistical aspects of big data and data science [MSC 2020]$3VANC026514$2MF 606 $a62J10$xAnalysis of variance and covariance (ANOVA) [MSC 2020]$3VANC026516$2MF 606 $a60B20$xRandom matrices (probabilistic aspects) [MSC 2020]$3VANC029326$2MF 610 $aBig Data$9KW:K 610 $aCovariance matrix estimation$9KW:K 610 $aHigh-dimensional asymptotics$9KW:K 610 $aHigh-dimensional covariance matrix estimation$9KW:K 610 $aHigh-dimensional statistics$9KW:K 610 $aLinear spectral statistics for high-dimensional inference$9KW:K 610 $aRandom matrix theory$9KW:K 610 $aSample covariance matrix estimator$9KW:K 610 $aShrinkage estimation of covariance matrices$9KW:K 610 $aStatistical inference$9KW:K 620 $aCH$dCham$3VANL001889 700 1$aZagidullina$bAygul$3VANV227259$01071981 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240614$gRICA 856 4 $uhttps://doi.org/10.1007/978-3-030-80065-9$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 $aVAN0274816 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-book 8262 $e08eMF8262 20240430 996 $aHigh-Dimensional Covariance Matrix Estimation$92568135 997 $aUNICAMPANIA