LEADER 02514nam0 22005413i 450 001 VAN00275481 005 20240806101542.705 017 70$2N$a9789811681622 100 $a20240429d2021 |0itac50 ba 101 $aeng 102 $aSG 105 $a|||| ||||| 200 1 $aNon-Gaussian Autoregressive-Type Time Series$fN. Balakrishna 210 $aSingapore$cSpringer$d2021 215 $axviii, 225 p.$cill.$d24 cm 606 $a62-XX$xStatistics [MSC 2020]$3VANC022998$2MF 606 $a62F10$xPoint estimation [MSC 2020]$3VANC021207$2MF 606 $a62F12$xAsymptotic properties of parametric estimators [MSC 2020]$3VANC030772$2MF 606 $a62J05$xLinear regression; mixed models [MSC 2020]$3VANC023156$2MF 606 $a62J12$xGeneralized linear models (logistic models) [MSC 2020]$3VANC025019$2MF 606 $a62M10$xTime series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020]$3VANC025079$2MF 610 $a(auto)regression$9KW:K 610 $aAutoregressive models with non Gaussian innovations$9KW:K 610 $aAutoregressive models with stable innovations$9KW:K 610 $aCauchy autoregressive models$9KW:K 610 $aEstimating function methods$9KW:K 610 $aExponential autoregressive models$9KW:K 610 $aGamma autoregressive models$9KW:K 610 $aLaplace autoregressive models$9KW:K 610 $aLogistic autoregressive models$9KW:K 610 $aMaximum probability estimators$9KW:K 610 $aMinification models$9KW:K 610 $aMixture autoregressive models$9KW:K 610 $aNon Gaussian time series$9KW:K 610 $aProduct autoregressive models$9KW:K 610 $aQuasi likelihood methods$9KW:K 610 $aTime series models with slowly varying innovations$9KW:K 620 $aSG$dSingapore$3VANL000061 700 1$aBalakrishna$bNarayana$3VANV227954$01736719 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20240906$gRICA 856 4 $uhttps://doi.org/10.1007/978-981-16-8162-2$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 $aVAN00275481 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08CONS e-Book 8517 $e08eMF8517 20240503 996 $aNon-Gaussian Autoregressive-Type Time Series$94156924 997 $aUNICAMPANIA