Riassunto
The book provides new developments in classification, data analysis and multidimensional methods, topics which are of central interest to modern Statistics. A wide range of topics is considered including methodologies in classification, fuzzy clustering, discrimination, regression tree, neural networks, proximity methodologies, factorial methods, spatial analysis, multiway and multivariate analysis.
Contenuti
Classification: Methodologies in Classification: A. Cerioli: Measuring the influence of individual observations and variables in cluster analysis.- P. D`Urso, M. G. Pittau: Consensus classification for a set of multiple time series.- T. Di Battista, D. Di Spalatro: A bootstrap method for adaptive cluster sampling.- D. Iezzi, M. Vichi: Forecasting a classification.- Fuzzy Clustering and Fuzzy Methods: A. Bellacicco: Neural networks as a fuzzy semantic network of events.- L. Cerbara: Hierarchical fuzzy clustering: an example of spatio-temporal analysis.- G. Iacovacci: A new algorithm for semi-fuzzy clustering.- A. Maturo, B. Ferri: Fuzzy classification and hyperstructures : an application to evaluation of urban projects.- M.A. Milioli: Variable selection in fuzzy clustering.- Other Approaches for Classification: Discrimination and Classification: M. Alfo, P. Postiglione: Discriminant analysis using markovian automodels.- F. Esposito, D. Malerba, G. Semeraro, S. Caggese: Discretization of continuous-valued data in symbolic classification learning.- S. Ingrassia: Logistic discrimination by Kullback-Leibler type distance measures.- A. Montanari, D. Calo: An empirical discrimination algorithm based on projection pursuit density estimation.- Regression Tree and Neural Networks: R. Miglio, M. Pillati: Notes on methods for improving unstable classifiers.- F. Mola: Selection of cut points in generalized additive models.- R. Siciliano: Latent budget trees for multiple classification.- Multivariate and Multidimensional Data Analysis: Proximity Analysis and Multidimensional Scaling: G. Bove, R. Rocci: Methods for asymmetric three-way scaling.- S. Camiz: Comparison of Euclidean approximation of non-Euclidean distances.- A. Montanari, G. Soffritti: Analysing dissimilarities through multigraphs.- C. Quintano: Professional positioning based on dominant eigenvalue scores (DES), dimensional scaling (DS) and multidimensional scaling (MDS) synthesis of binary evaluations matrix of experts.- M. Vichi: Non-metric full-multidimensional scaling.- Factorial Methods: I. Corazziari: Dynamic factor analysis.- V. Esposito, G. Scepi: A non symmetrical generalised co-structure analysis for inspecting quality control data.- R. Lombardo, G. Tessitore: Principal surfaces constrained analysis.- R. Verde: Generalised canonical analysis on symbolic objects.- G. Vittadini: Analysis of qualitative variables in structural models with unique solutions.- Spatial Analysis: A. Capobianchi: Exploring multivariate spatial data: line transect data.- A. Giusti, A. Petrucci: On the assessment of geographical survey units using constrained classification.- L. Romagnoli: Kalman filter applied to non-causal models for spatial data.- Multiway Data Analysis: S. Bolasco, A. Morrone, F. Baiocchi: A paradigmatic path for statistical content analysis using an integrated package of textual data treatment.- M. Chiodi, A. M. Mineo: The analysis of auxological data by means of nonlinear multivariate growth curves.- M. Coli, L. Ipploliti, E. Nissi: The Kalman filter on three-way data matrix for missing data: a case study on sea water pollution.- P.A. Cornillon, P. Amenta, R. Sabatier: Three-way data arrays with double neighborhood relations as a tool to analyze a contiguity structure.- A. Lemmi, D. Stefano Gazzei: Firm performance analysis with panel data.- Multivariate Data Analysis: M.R. D`Esposito, G. Ragozini: Detection of multivariate outliers by convex hulls.- M. Di Marzio, G. Lafratta: Reducing dimensionality effects on kernel density estimation: the bivariate gaussi
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