LEADER 00959nam0-2200265 --450 001 9910492353303321 005 20210902101728.0 010 $a978-88-297-1259-5 100 $a20210902d2021----kmuy0itay5050 ba 101 2 $aita$aeng 102 $aIT 105 $aa 001yy 200 1 $a<>altra opportunitā per l'architettura$eil nuovo Rettorato dell'Universitā degli Studi della Campania Luigi Vanvitelli$fCherubino Gambardella 210 $aVenezia$cMarsilio$d2021 215 $a127 p.$cin gran parte ill.$d25 cm 300 $aTesto in italiano e inlgese 510 1 $aAnother oppurtunity for architecture$ethe new Rettorato of the University of Campania Luigi Vanvitelli 700 1$aGambardella,$bCherubino$010814 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910492353303321 952 $aSEZ.NA B 3699$b905/2021$fFARBC 959 $aFARBC 996 $aAltra opportunitā per l'architettura$91865960 997 $aUNINA LEADER 05231nam 22008895 450 001 9910735775003321 005 20250610112328.0 010 $a9783031301643$b(ebook) 010 $a3031301641 024 7 $a10.1007/978-3-031-30164-3 035 $a(MiAaPQ)EBC30663111 035 $a(Au-PeEL)EBL30663111 035 $a(DE-He213)978-3-031-30164-3 035 $a(PPN)272250392 035 $a(CKB)27857483200041 035 $a(OCoLC)1391442935 035 $a(EXLCZ)9927857483200041 100 $a20230724d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aStatistical Models and Methods for Data Science /$fedited by Leonardo Grilli, Monia Lupparelli, Carla Rampichini, Emilia Rocco, Maurizio Vichi 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (viii, 188 pages) $cillustrations 225 1 $aStudies in Classification, Data Analysis, and Knowledge Organization,$x2198-3321 300 $aIncludes author index. 311 08$aPrint version: Grilli, Leonardo Statistical Models and Methods for Data Science Cham : Springer International Publishing AG,c2023 9783031301636 327 $aClustering financial time series by dependency -- The Homogeneity Index as a Measure of Interrater Agreement for Ratings on a Nominal Scale -- Hierarchical clustering of income data based on share densities -- Optimal Coding of High Cardinality Categorical Data in Machine Learning -- Bayesian Multivariate Analysis of Mixed data -- Marginals matrix under a generalized Mallows model based on the power divergence -- Time series clustering based on forecast distributions: an empirical analysis on production indices for construction -- Partial Reconstruction of Measures from Halfspace Depth -- Posterior Predictive Assessment of IRT Models via the Hellinger Distance: A Simulation Study -- Shapley Lorenz values for credit risk management -- A study of lack-of-fit diagnostics for models fit to cross-classified binary variables -- Robust Response Transformations for Generalized Additive Models via Additivity and Variance Stabilisation -- A Random-Coefficients Analysis with a Multivariate Random-Coefficients Linear Model -- Parsimonious mixtures of matrix-variate shifted exponential normal distributions. 330 $aThis book focuses on methods and models in classification and data analysis and presents real-world applications at the interface with data science. Numerous topics are covered, ranging from statistical inference and modelling to clustering and factorial methods, and from directional data analysis to time series analysis and small area estimation. The applications deal with new developments in a variety of fields, including medicine, finance, engineering, marketing, and cyber risk. The contents comprise selected and peer-reviewed contributions presented at the 13th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society, CLADAG 2021, held (online) in Florence, Italy, on September 9?11, 2021. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results at the interface between classification and data science. 410 0$aStudies in Classification, Data Analysis, and Knowledge Organization,$x2198-3321 606 $aMathematical statistics$xData processing 606 $aQuantitative research 606 $aMachine learning 606 $aStatistics 606 $aStatistics 606 $aArtificial intelligence$xData processing 606 $aStatistics and Computing 606 $aData Analysis and Big Data 606 $aStatistical Learning 606 $aStatistical Theory and Methods 606 $aApplied Statistics 606 $aData Science 606 $aDades massives$2thub 606 $aEstadística matemātica$2thub 608 $aCongressos$2thub 608 $aLlibres electrōnics$2thub 615 0$aMathematical statistics$xData processing. 615 0$aQuantitative research. 615 0$aMachine learning. 615 0$aStatistics. 615 0$aStatistics. 615 0$aArtificial intelligence$xData processing. 615 14$aStatistics and Computing. 615 24$aData Analysis and Big Data. 615 24$aStatistical Learning. 615 24$aStatistical Theory and Methods. 615 24$aApplied Statistics. 615 24$aData Science. 615 7$aDades massives 615 7$aEstadística matemātica 676 $a005.7 676 $a005.7 702 $aGrilli$b Leonardo 702 $aLupparelli$b Monia 702 $aRampichini$b Carla 702 $aRocco$b Emilia 702 $aVichi$b Maurizio$f1959- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910735775003321 996 $aStatistical Models and Methods for Data Science$93417113 997 $aUNINA