Zani / Cerioli / Riani Data Analysis, Classification and the Forward Search

Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Parma, June 6-8, 2005
1. Auflage 2007
ISBN: 978-3-540-35978-4
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 426 Seiten

This volume contains revised versions of selected papers presented at the biennial meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, which was held in Parma, June 6-8, 2005. Sergio Zani chaired the Scientific Programme Committee and Andrea Cerioli chaired the Local Organizing Committee. The scientific programme of the conference included 127 papers, 42 in spe cialized sessions, 68 in contributed paper sessions and 17 in poster sessions. Moreover, it was possible to recruit five notable and internationally renowned invited speakers (including the 2004-2005 President of the International Fed eration of Classification Societies) for plenary talks on their current research work. Among the specialized sessions, two were organized by Wolfgang Gaul with five talks by members of the GfKl (German Classification Society), and one by Jacqueline J. Meulman (Dutch/Flemish Classification Society). Thus, the conference provided a large number of scientists and experts from home and abroad with an attractive forum for discussion and mutual exchange of knowledge. The topics of all plenary and specialized sessions were chosen to fit, in the broadest possible sense, the mission of CLADAG, the aim of which is "to further methodological, computational and applied research within the fields of Classification, Data Analysis and Multivariate Statistics". A peer-review refereeing process led to the selection of 46 extended papers, which are contained in this book.

Autoren/Hrsg.

Zani, Sergio

Cerioli, Andrea

Riani, Marco

Vichi, Maurizio

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;Clustering and Discrimination;13
3.1;Genetic Algorithms- based Approaches for Clustering Time Series;14
3.2;On the Choice of the Kernel Function in Kernel Discriminant Analysis Using Information Complexity;22
3.3;Growing Clustering Algorithms in Market Segmentation: Defining Target Groups and Related Marketing Communication;33
3.4;Graphical Representation of Functional Clusters and MDS Configurations;41
3.5;Estimation of the Structural Mean of a Sample of Curves by Dynamic Time Warping;48
3.6;Sequential Decisional Discriminant Analysis;58
3.7;Regularized Sliced Inverse Regression with Applications in Classification;67
4;Multidimensional Data Analysis and Multivariate Statistics;75
4.1;Approaches to Asymmetric Multidimensional Scaling with External Information;76
4.2;Variable Architecture Bayesian Neural Networks: Model Selection Based on EMC;84
4.3;Missing Data in Optimal Scaling;92
4.4;Simple Component Analysis Based on RV Coefficient;100
4.5;Baum-Eagon Inequality in Probabilistic Labeling Problems;109
4.6;Monotone Constrained EM Algorithms for Multinomial Mixture Models;117
4.7;Visualizing Dependence of Bootstrap Confidence Intervals for Methods Yielding Spatial Configurations;125
4.8;Automatic Discount Selection for Exponential Family State-Space Models;133
4.9;A Generalization of the Polychoric Correlation Coefficient;141
4.10;The Effects of MEP Distributed Random Effects on Variance Component Estimation in Multilevel Models;149
4.11;Calibration Confidence Regions Using Empirical Likelihood;159
5;Robust Methods and the Forward Search;167
5.1;Random Start Forward Searches with Envelopes for Detecting Clusters in Multivariate Data;168
5.2;Robust Transformation of Proportions Using the Forward Search;177
5.3;The Forward Search Method AppUed to Geodetic Transformations;185
5.4;An R Package for the Forward Analysis of Multivariate Data;193
5.5;A Forward Search Method for Robust Generahsed Procrustes Analysis;202
5.6;A Projection Method for Robust Estimation and Clustering in Large Data Sets;212
5.7;Robust Multivariate Calibration;220
6;Data Mining Methods and Software;228
6.1;Procrustes Techniques for Text Mining;229
6.2;Building Recommendations from Random Walks on Library OPAC Usage Data;237
6.3;A Software Tool via Web for the Statistical Data Analysis: R-php;249
6.4;Evolutionary Algorithms for Classification and Regression Trees;257
6.5;Variable Selection Using Random Forests;265
6.6;Boosted Incremental Tree-based Imputation of Missing Data;273
6.7;Sensitivity of Attributes on the Performance of Attribute-Aware Collaborative Filtering;281
7;Multivariate Methods for Customer Satisfaction and Service Evaluation;289
7.1;Customer Satisfaction Evaluation: An Approach Based on Simultaneous Diagonalization;290
7.2;Analyzing Evaluation Data: Modelling and Testing for Homogeneity;299
7.3;Archetypal Analysis for Data Driven Benchmarking;308
7.4;Determinants of Secondary School Dropping Out: a Structural Equation Model;318
7.5;Testing Procedures for Multilevel Models with Administrative Data;328
7.6;Multidimensional Versus Unidimensional Models for Ability Testing;337
8;Multivariate Methods in Applied Science;345
8.1;A Spatial Mixed Model for Sectorial Labour Market Data;346
8.2;The Impact of the New Labour Force Survey on the Employed Classification;355
8.3;Using CATPCA to Evaluate Market Regulation;364
8.4;Credit Risk Management Through Robust Generalized Linear Models;372
8.5;Classification of Financial Returns According to Thresholds Exceedances;382
8.6;Nonparametric Clustering of Seismic Events;392
8.7;A Non- Homogeneous Poisson Based Model for Daily Rainfall Data;400
8.8;A Comparison of Data Mining Methods and Logistic Regression to Determine Factors Associated with Death Following Injury;412
9;Author Index;419