Fichet Bernard et al. Classification and Multivariate Analysis for Complex Data Structures

Springer Science & Business Media, 2011. — 473 p. — ISBN: 978-3-642-13311-4.The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest advances in data analysis methods for multidimensional data which can present a complex structure: The book offers a selection of papers presented at the first Joint Meeting of the Société Francophone de Classification and the Classification and Data Analysis Group of the Italian Statistical Society. Special attention is paid to new methodological contributions from both the theoretical and the applicative point of views, in the fields of Clustering, Classification, Time Series Analysis, Multidimensional Data Analysis, Knowledge Discovery from Large Datasets, Spatial Statistics.Key Notes
Edwin Diday
Principal Component Analysis for Categorical Histogram Data: Some Open Directions of Research
Giuseppe Giordano, Carlo Natale Lauro, and Germana Scepi
Factorial Conjoint Analysis Based Methodologies
Jacqueline J. Meulman, Lawrence J. Hubert, and Phipps Arabie
Ordering and Scaling Objects in Multivariate Data Under Nonlinear Transformations of Variables
Paolo Giudici and Emanuele Dequarti
Statistical Models to Predict Academic Churn Risk
André Hardy
The Poisson Processes in Cluster Analysis
Roberta Siciliano and Massimo Aria
TWO-CLASS Trees for Non-Parametric Regression Analysis
Classification and Discrimination
Miguel Fernández, Cristina Rueda, and Bonifacio Salvador
Efficient Incorporation of Additional Information to Classification Rules
Umberto Magagnoli and Gabriele Cantaluppi
The Choice of the Parameter Values in a Multivariate Model of a Second Order Surface with Heteroscedastic Error
Isabella Morlini
Mixed Mode Data Clustering: An Approach Based on Tetrachoric Correlations
Valerio A. Tutore
Optimal Scaling Trees for Three-Way Data
Data Mining
Concetto Elvio Bonafede and Paola Cerchiello
A Study on Text Modeling via Dirichlet Compound Multinomial
D. Bruzzese and U. Giani
Automatic Multilevel Thresholding Based on a Fuzzy Entropy Measure
Daniela G. Calò
Some Developments in Forward Search Clustering
Domenico De Stefano
Spectral Graph Theory Tools for Social Network Comparison
Mauro Iacono and Antonio Irpino
Improving the MHIST-p Algorithm for Multivariate Histograms of Continuous Data
Julien Lavergne, Hanane Azzag, Christiane Guinot, and Gilles Venturini
On Building and Visualizing Proximity Graphs for Large Data Sets with Artificial Ants
Mariagiulia Matteucci and Bernard P. Veldkamp
Including Empirical Prior Information in Test Administration
Robustness and Classification
Matilde Bini and Margherita Velucchi
Italian Firms’ Geographical Location in High-tech Industries: A Robust Analysis
Aldo Corbellini and Lisa Crosato
Robust Tests for Pareto Density Estimation
Agostino Di Ciaccio
Bootstrap and Nonparametric Predictors to Impute Missing Data
Giovanna Menardi, Federico Tedeschi and Nicola Torelli
On the Use of Boosting Procedures to Predict the Risk of Default
Categorical Data and Latent Class Approach
Marcella Corduas
Assessing Similarity of Rating Distributions by Kullback-Leibler Divergence
Michele Costa and Luca De Angelis
Sector Classification in Stock Markets: A Latent Class Approach
Carles M. Cuadras and Daniel Cuadras
Partitioning the Geometric Variability in Multivariate Analysis and Contingency Tables
Luigi Fabbris
One-Dimensional Preference Data Imputation Through Transition Rules
Giulio D’Epifanio
About a Type of Quasi Linear Estimating Equation Approach
Leonardo Grilli
Causal Inference Through Principal Stratification: A Special Type of Latent Class Modeling
Isabella Sulis, Mariano Porcu, and Marco Pitzalis
Scaling the Latent Variable Cultural Capital via Item Response Models and Latent Class Analysis
Laura Trinchera
Assessment of Latent Class Detection in PLS Path Modeling: a Simulation Study to Evaluate the Group Quality Index performance
Latent Variables and Related Methods
Giuseppe Boari, Gabriele Cantaluppi, and Stefano Bertelli
Non-Linear Relationships in SEM with Latent Variables: Some Theoretical Remarks and a Case Study
Marine Cadoret, Sébastien Lê, and Jérôme Pagès
Multidimensional Scaling Versus Multiple Correspondence Analysis When Analyzing Categorization Data
Antonio D’Ambrosio and Marcello Pecoraro
Multidimensional Scaling as Visualization Tool of Web Sequence Rules
Antonio Forcina
Partial Compliance, Effect of Treatment on the Treated and Instrumental Variables
C. Lauro, D. Nappo, M.G. Grassia, and R. Miele
Method of Quantification for Qualitative Variables and their Use in the Structural Equations Models
Rosaria Romano, Jannie S. Vestergaard, Mohsen Kompany-Zareh, and Wender L.P. Bredie
Monitoring Panel Performance Within and Between Sensory Experiments by Multi-Way Analysis
Giorgio Russolillo and Carlo Natale Lauro
A Proposal for Handling Categorical Predictors in PLS Regression Framework
Symbolic, Multivalued and Conceptual Data Analysis
Maria Rosaria D’Esposito, Francesco Palumbo, and Giancarlo Ragozini
On the Use of Archetypes and Interval Coding in Sensory Analysis
Marina Marino and Simona Signoriello
From Histogram Data to Model Data Analysis
Jaromír Antoch and Raffaele Miele
Use of Genetic Algorithms When Computing Variance of Interval Data
Michel Soto, Bénédicte Le Grand, and Marie-Aude Aufaure
Spatial Visualization of Conceptual Data
Spatial, Temporal, Streaming and Functional Data Analysis
R. Abdesselam, S. Cieply and A.L. Le Nadant
A Test of LBO Firms’ Acquisition Rationale: The French Case
Giada Adelfio and Marcello Chiodi
Kernel Intensity for Space-Time Point Processes with Application to Seismological Problems
Antonio Balzanella, Elvira Romano, and Rosanna Verde
Summarizing and Mining Streaming Data via a Functional Data Approach
Francesco Giordano, Michele La Rocca, and Maria Lucia Parrella
Clustering Complex Time Series Databases
Massimo Mucciardi
Use of a Flexible Weight Matrix in a Local Spatial Statistic
Fabrice Rossi and Yves Lechevallier
Constrained Variable Clustering and the Best Basis Problem in Functional Data Analysis
Bio and Health Science
Luigi Augugliaro and Angelo M. Mineo
Plaid Model for Microarray Data: an Enhancement of the Pruning Step
Abdoulaye Baniré Diallo, Dunarel Badescu, Mathieu Blanchette, and Vladimir Makarenkov
Classification of the Human Papilloma Viruses
Mehdi Kaytoue, Sébastien Duplessis, and Amedeo Napoli
Toward the Discovery of Itemsets with Significant Variations in Gene Expression Matrices