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001438262 001__ 1438262
001438262 003__ OCoLC
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001438262 020__ $$a9783030699444$$q(electronic bk.)
001438262 020__ $$a3030699447$$q(electronic bk.)
001438262 020__ $$z9783030699437
001438262 020__ $$z3030699439
001438262 0247_ $$a10.1007/978-3-030-69944-4$$2doi
001438262 035__ $$aSP(OCoLC)1260401139
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001438262 049__ $$aISEA
001438262 050_4 $$aQA276.A1$$bS73 2021
001438262 08204 $$a519.5$$223
001438262 24500 $$aStatistical learning and modeling in data analysis :$$bmethods and applications /$$cSimona Balzano, Giovanni C. Porzio, Renato Salvatore, Domenico Vistocco, Maurizio Vichi, editors.
001438262 264_1 $$aCham :$$bSpringer,$$c[2021]
001438262 264_4 $$c©2021
001438262 300__ $$a1 online resource :$$billustrations (some color)
001438262 336__ $$atext$$btxt$$2rdacontent
001438262 337__ $$acomputer$$bc$$2rdamedia
001438262 338__ $$aonline resource$$bcr$$2rdacarrier
001438262 347__ $$atext file
001438262 347__ $$bPDF
001438262 4901_ $$aStudies in classification, data analysis, and knowledge organization,$$x1431-8814
001438262 5050_ $$aChapter 1 -- Interpreting Effects in Generalized Linear Modeling (Alan Agresti, Claudia Tarantola, and Roberta Varriale) -- Chapter 2 -- ACE, AVAS and Robust Data Transformations: Performance of Investment Funds (Anthony C. Atkinson, Marco Riani, Aldo Corbellini, and Gianluca Morelli) -- Chapter 3 -- Predictive Principal Component Analysis (Simona Balzano, Maja Bozic, Laura Marcis, and Renato Salvatore) -- Chapter 4 -- Robust model-based learning to discover new wheat varieties and discriminate adulterated kernels in X-ray images (Andrea Cappozzo, Francesca Greselin, and Thomas Brendan Murphy) -- Chapter 5 -- A dynamic model for ordinal time series: an application to consumers' perceptions of inflation (Marcella Corduas) -- Chapter 6 -- Deep learning to jointly analyze images and clinical data for disease detection (Federica Crobu and Agostino Di Ciaccio) -- Chapter 7 -Studying Affiliation Networks through Cluster CA and Blockmodeling (Daniela D'Ambrosio, Marco Serino, and Giancarlo Ragozini) -- Chapter 8 -- Sectioning Procedure on Geostatistical Indices Series of Pavement Road Profiles (Mauro D'Apuzzo, Rose-Line Spacagna, Azzurra Evangelisti, Daniela Santilli, and Vittorio Nicolosi) -- Chapter 9 -- Directional supervised learning through depth functions: an application to ECG waves analysis (Houyem Demni) -- Chapter 10 -- Penalized vs. contrained approaches for clusterwise linear regression modelling (Roberto Di Mari, Stefano Antonio Gattone, and Roberto Rocci) -- Chapter 11 -- Effect measures for group comparisons in a two-component mixture model: a cyber risk analysis (Maria Iannario and Claudia Tarantola) -- Chapter 12 -- A Cramér-von Mises test of uniformity on the hypersphere (Eduardo García-Portugués, Paula Navarro-Esteban, and Juan Antonio Cuesta-Albertos) -- Chapter 13 -- On mean and/or variance mixtures of normal distributions (Sharon X. Lee and Geoffrey J. McLachlan) -- Chapter 14 -- Robust depth-based inference in elliptical models (Stanislav Nagy and Jiří Dvořák) -- Chapter 15 -- Latent class analysis for the derivation of marketing decisions: An empirical study for BEV battery manufacturers (Friederike Paetz) -- Chapter 16 -- Small Area Estimation Diagnostics: the Case of the Fay-Herriot Model (Maria Chiara Pagliarella) -- Chapter 17 -- A comparison between methods to cluster mixed-type data: Gaussian mixtures versus Gower distance (Monia Ranalli and Roberto Rocci) -- Chapter 18 -- Exploring the gender gap in Erasmus student mobility flows (Marialuisa Restaino, Ilaria Primerano, and Maria Prosperina Vitale).
001438262 506__ $$aAccess limited to authorized users.
001438262 520__ $$aThe contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications. The book covers numerous research topics, ranging from statistical inference and modeling to clustering and factorial methods, from directional data analysis to time series analysis and small area estimation. The applications reflect new analyses in a variety of fields, including medicine, finance, engineering, marketing and cyber risk. The book gathers selected and peer-reviewed contributions presented at the 12th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2019), held in Cassino, Italy, on September 11-13, 2019. CLADAG promotes advanced methodological research in multivariate statistics with a special focus on data analysis and classification, and supports the exchange and dissemination of ideas, methodological concepts, numerical methods, algorithms, and computational and applied results. This book, true to CLADAG's goals, is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification.
001438262 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 30, 2021).
001438262 650_0 $$aStatistics$$vCongresses.
001438262 650_0 $$aMathematical models$$vCongresses.
001438262 650_6 $$aModèles mathématiques$$vCongrès.
001438262 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001438262 655_7 $$aConference papers and proceedings.$$2lcgft
001438262 655_7 $$aActes de congrès.$$2rvmgf
001438262 655_7 $$aCongressos.$$2thub
001438262 655_7 $$aLlibres electrònics.$$2thub
001438262 655_0 $$aElectronic books.
001438262 7001_ $$aBalzano, Simona,$$eeditor.
001438262 7001_ $$aPorzio, Giovanni C.,$$eeditor.
001438262 7001_ $$aSalvatore, Renato,$$eeditor.
001438262 7001_ $$aVistocco, Domenico,$$eeditor.
001438262 7001_ $$aVichi, Maurizio,$$d1959-$$eeditor.
001438262 7102_ $$aSocietà italiana di statistica.$$bRiunione scientifica$$n(12th :$$d2019 :$$cCassino, Italy)
001438262 77608 $$iPrint version:$$z3030699439$$z9783030699437$$w(OCoLC)1233166058
001438262 830_0 $$aStudies in classification, data analysis, and knowledge organization.$$x1431-8814
001438262 852__ $$bebk
001438262 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-69944-4$$zOnline Access$$91397441.1
001438262 909CO $$ooai:library.usi.edu:1438262$$pGLOBAL_SET
001438262 980__ $$aBIB
001438262 980__ $$aEBOOK
001438262 982__ $$aEbook
001438262 983__ $$aOnline
001438262 994__ $$a92$$bISE