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Data Analysis and Classification
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Table of Contents

Actuarial and Continuous Time Risk Models: Towards a Synthesis.- Clustering of High-Dimensional and Correlated Data.- Statistical Methods for Cryptography.- An algorithm for earthquakes clustering based on maximum likelihood.- A two-step iterative procedure for clustering of binary sequences.- Clustering linear models using Wasserstein distance.- Comparing approaches for clustering mixed mode data: an application in marketing research.- The Progressive Single Linkage Algorithm Based on Minkowski Ultrametrics.- Visualization of model-based clustering structures.- Models for Asymmetry in Proximity Data.- Intimate femicide in Italy: a model to classify how killings happened.- Two-Dimensional Centrality of Asymmetric Social Network.- The forward search for classical multidimensional scaling when the starting data matrix is known.- Discriminant Analysis on Mixed Predictos.- A Statistical Calibration Model for Affymetrix Probe Level Data.- A proposal to fuzzify categorical variables in operational risk management.- Common Optimal Scaling for Customer Satisfaction Models: a point to Cobb-Douglas' form.- Structural Neural Networks for Modeling Customer Satisfaction.- Dimensionality of scores obtained with a paired-comparison tournament system of questionnaire items.- Using Rasch measurement to assess the role of the traditional family in Italy.- Projection pursuit using the adjusted critical bandwidth.- Association rule mining of multimedia content.- Automatic dictionary and rule-based systems for extracting information from text.- Several computational studies about variable selection for probabilistic Bayesian classifiers.- Semantic classification and cooccurrences: a method for the rules production for the information extraction from textual data.- The effectiveness of university education: a structural equation model.- Simultaneous Threshold Interaction Detection in Binary Classification.- Detecting Subset of Classifiers for Multi-Attribute Response Prediction.- Clustering Textual Data by Latent Dirichlet Allocation: Applications and Extensions to Hierarchical Data.- Multilevel Latent Class Models for evaluation of long term care facilities.- Author-Coauthor Social Networks and Emerging Scientific Subfields.- A hierarchical Model for Time Dependent Multivariate Longitudinal Data.- Covariate error bias effects in dynamic regression model estimation and improvement in the prediction by covariate local clusters.- Local Multilevel Modeling for Comparisons of Institutional Performance.- Modelling Network Data: an Introduction to Exponential Random Graph Models.- Earthquakes clustering interpretation based on a second-order diagnostic approach.- Latent regression in Rasch framework.- A Multilevel Latent Variable Model for Multidimensional Longitudinal Data.- Turning Point Detection Using Markov Switching Models with Latent Information.- Statistical and Numerical Algorithms for Time Series Classification.- Mining Time Series Data: a selective survey.- Predictive dynamic models for SMEs.- Clustering Algorithms for Large Temporal Data Sets.- Robust Clustering for Performance Evaluation.- Outliers detection strategy for a Robust Curves Clustering.- Robust fuzzy classification.- Weighted Likelihood Inference for a Mixed Regressive Spatial Autoregressive Model.- Detecting Price Outliers in European Trade Data with Backward and Forward Methods.- Comparing continuous treatment matching methods in policy evaluation.- Temporal aggregation and closure of VARMA models. Some new results.- An index for ranking financial portfolios according to internal turnover.- Bayesian Hidden Markov Models for Financial Data.- Regression imputation for Space-Time datasets with missing values.- A multiple imputation approach in a survey on university teaching evaluation.

Reviews

From the reviews: "It covers a wide array of topics, including methods for classification and clustering, statistical models, statistical multivariate methods, data mining, both financial and economic applications, and knowledge extraction from temporal data. ... the organization and structure of the remainder of the book is good and logical. ... the volume provides a good variety of applications in various fields. Combining theoretical advances with a host of real applications, this volume will be of equally special interest for researchers and practitioners." (Technometrics, Vol. 53 (3), August, 2011)

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