Advances in statistical models for data analysis. (2015)

• Record Type: Book
• Further Information: Note: Isabella Morlini, Tommaso Minerva, Maurizio Vichi, editors.
• Editors: Morlini, Isabella; Minerva, Tommaso; Vichi, Maurizio
• Contents: 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.
• Publisher Details: Cham : Springer
• Publication Date: 2015
• Extent: 1 online resource
• Subjects: 519.5; Statistics; Mathematical statistics; Data mining; MATHEMATICS -- Applied; MATHEMATICS -- Probability & Statistics -- General; Data mining; Mathematical statistics; Statistics; Statistical Theory and Methods; Statistics and Computing/Statistics Programs; Statistics for Business/Economics/Mathematical Finance/Insurance; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Computers -- Mathematical & Statistical Software; Business & Economics -- Statistics; Social Science -- Statistics; Mathematical & statistical software; Probability & statistics; Social research & statistics; Electronic books
• Languages: English
• ISBNs: 9783319173771; 3319173774; 3319173766; 9783319173764
• Related ISBNs: 9783319173764
• Notes: Note: Includes bibliographical references at the end of each chapters.; Note: Online resource; title from PDF title page (EBSCO, viewed September 11, 2015).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.