05231nam 22008895 450 991073577500332120250610112328.09783031301643(ebook)303130164110.1007/978-3-031-30164-3(MiAaPQ)EBC30663111(Au-PeEL)EBL30663111(DE-He213)978-3-031-30164-3(PPN)272250392(CKB)27857483200041(OCoLC)1391442935(EXLCZ)992785748320004120230724d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierStatistical Models and Methods for Data Science /edited by Leonardo Grilli, Monia Lupparelli, Carla Rampichini, Emilia Rocco, Maurizio Vichi1st ed. 2023.Cham :Springer International Publishing :Imprint: Springer,2023.1 online resource (viii, 188 pages) illustrationsStudies in Classification, Data Analysis, and Knowledge Organization,2198-3321Includes author index.Print version: Grilli, Leonardo Statistical Models and Methods for Data Science Cham : Springer International Publishing AG,c2023 9783031301636 Clustering 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.This 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.Studies in Classification, Data Analysis, and Knowledge Organization,2198-3321Mathematical statisticsData processingQuantitative researchMachine learningStatisticsStatisticsArtificial intelligenceData processingStatistics and ComputingData Analysis and Big DataStatistical LearningStatistical Theory and MethodsApplied StatisticsData ScienceDades massivesthubEstadística matemàticathubCongressosthubLlibres electrònicsthubMathematical statisticsData processing.Quantitative research.Machine learning.Statistics.Statistics.Artificial intelligenceData processing.Statistics and Computing.Data Analysis and Big Data.Statistical Learning.Statistical Theory and Methods.Applied Statistics.Data Science.Dades massivesEstadística matemàtica005.7005.7Grilli LeonardoLupparelli MoniaRampichini CarlaRocco EmiliaVichi Maurizio1959-MiAaPQMiAaPQMiAaPQBOOK9910735775003321Statistical Models and Methods for Data Science3417113UNINA