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＜電子ブック＞
Advances in Statistical Models for Data Analysis / edited by Isabella Morlini, Tommaso Minerva, Maurizio Vichi
(Studies in Classification, Data Analysis, and Knowledge Organization. ISSN:21983321)

版	1st ed. 2015.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2015
本文言語	英語
大きさ	VIII, 268 p. 49 illus., 13 illus. in color : online resource
著者標目	Morlini, Isabella editor Minerva, Tommaso editor Vichi, Maurizio editor SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Mathematical statistics -- Data processing  全ての件名で検索 LCSH:Social sciences -- Statistical methods  全ての件名で検索 FREE:Statistical Theory and Methods FREE:Statistics and Computing FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy
一般注記	Using the dglars Package to Estimate a Sparse Generalized Linear Model -- A Depth function for Geostatistical Functional Data -- Robust Clustering of EU Banking Data -- Sovereign Risk and Contagion Effects in the Eurozone: a Bayesian Stochastic Correlation Model -- Female Labour Force Participation and Selection Effect: Southern vs Eastern European Countries -- Asymptotics in Survey Sampling for High Entropy Sampling Design -- A Note On the Use of Recursive Partitioning in Causal Inference -- Meta-Analysis of Poll Accuracy Measures: A Multilevel Approach -- Families of Parsimonious Finite Mixtures of Regression Models -- Quantile Regression for Clustering and Modeling Data -- Non-metric MDS Consensus Community Detection -- The performance of the Gradient-like Influence Measure in Generalized Linear Mixed Models -- New Flexible Probability Distributions for Ranking Data -- Robust Estimation of Regime Switching Models -- Incremental Visualization of Categorical Data -- A new Proposal for Tree Model Selection and Visualization -- Object-Oriented Bayesian Network to Deal with Measurement Error in Household Surveys -- Comparing Fuzzy and Multidimensional Methods to Evaluate Well-being in European Regions -- Cluster Analysis of Three-way Atmospheric Data -- Asymmetric CLUster Analysis Based on SKEW-symmetry: ACLUSKEW -- Parsimonious Generalized Linear Gaussian Cluster-Weighted Models -- New perspectives for the MDC Index in Social Research Fields -- Clustering Methods for Ordinal Data: A Comparison Between Standard and New Approaches -- Novelty Detection with One-class Support Vector Machines -- Using Discrete-time  Multi-State Models to Analyze  Students' University Pathways This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy HTTP:URL=https://doi.org/10.1007/978-3-319-17377-1

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