<p>From the reviews:</p><p>“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)</p>
This volume contains revised versions of selected papers presented at the biennial meeting of the Classi?cation and Data Analysis Group (CLADAG) of the Italian Statistical Society, which was held in Macerata, September 12-14, 2007. Carlo Laurochairedthe Scienti?c ProgrammeCommitteeand FrancescoPalumbochaired the Local Organizing Committee. The scienti?c programme scheduled 150 oral presentations and one poster s- sion. Sessions were organised in ?ve plenary sessions, 10 invited paper specialised sessions and 24 solicited paper sessions. Contributed papers and posters were 54 and 12, respectively. Five eminent scholars, who have given important impact in the Classi?cation and Data Analysis ?elds, were invited as keynote speakers, they are H. Bozdogan, S. R. Masera, G. McLachlan, A. Montanari, A. Rizzi. Invited Paper Specialised Sessions focused on the following topics: Knowledge extraction from temporal data models Statistical models with errors-in-covariates Multivariate analysis for microarray data Cluster analysis of complex data Educational processes assessment by means of latent variables models Classi?cation of complex data Multidimensional scaling Statistical models for public policies Classi?
cation models for enterprise risk management Model-based clustering It is worth noting that two of the ten specialised sessions were organised by the French (Classi?cation of complex data) and Japanese (Multidimensional scaling) classi?cation societies. The SPC is grateful to professorsOkada (Japan) and Zighed (France), who took charge of the Japanese and French specialised session org- isation, respectively.
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Key-note.- Clustering of High-Dimensional and Correlated Data.- Statistical Methods for Cryptography.- Cluster Analysis.- 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.- Multivariate Analysis and Application.- 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.- Multivariate Analysis and Application.- Discriminant Analysis on Mixed Predictors.- 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.- Preserving the Clustering Structure by a Projection Pursuit Approach.- Association Rule Mining of Multimedia Content.- Classification and Classification Tree.- Automatic Dictionary- and Rule-Based Systems for Extracting Information from Text.- Several Computational Studies About Variable Selection for Probabilistic Bayesian Classifiers.- Semantic Classification and Co-occurrences: AMethod 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.- Statistical Models.- 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.- Latent Variables.- An Analysis of Earthquakes Clustering 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.- Knowledge Extraction from Temporal Data.- 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.- Outlier Detection and Robust Methods.- Robust Clustering for Performance Evaluation.- Outliers Detection Strategy for a Curve Clustering Algorithm.- Robust Fuzzy Classification.- Weighted Likelihood Inference for a Mixed Regressive Spatial Autoregressive Model.- Detecting Price Outliers in European Trade Data with theForward Search.- Statistical Methods for Financial and Economics Data.- 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.- Missing Values.- Regression Imputation for Space-Time Datasets with Missing Values.- A Multiple Imputation Approach in a Survey on University Teaching Evaluation.
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The volume provides results from the latest methodological developments in data analysis and classification and highlights new emerging subjects within the field. It contains articles about statistical models, classification, cluster analysis, multidimensional scaling, multivariate analysis, latent variables, knowledge extraction from temporal data, financial and economic applications, and missing values. Papers cover both theoretical and empirical aspects.
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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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Includes supplementary material: sn.pub/extras
Produktdetaljer
ISBN
9783642037382
Publisert
2009-12-16
Utgiver
Vendor
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet