Data Analysis, Classification And the Forward Search

by Zani, Sergio; Cerioli, Andrea; Riani, Marco; Vichi, Maurizio

• ISBN13: 9783540359777
• ISBN10: 354035977X
• Format: Paperback
• Copyright: 2006-10-30
• Publisher: Springer Verlag

Summary

The book presents new developments in data analysis, classification and multivariate statistics, and in their algorithmic implementation. The more methodologically oriented reader will find contributions to the theory of clustering and discrimination, multidimensional data analysis, data mining, and robust statistics with a special emphasis on the novel Forward Search approach. Many papers also provide significant contributions in a wide range of fields of application. Customer satisfaction and service evaluation are two examples of such emerging fields.

Table of Contents

Genetic algorithms-based approaches for clustering time series	p. 5
On the choice of the kernel function in kernel discriminant analysis using information complexity	p. 11
Growing clustering algorithms in market segmentation : defining target groups and related marketing communication	p. 23
Graphical representation of functional clusters and MDS configurations	p. 31
Estimation of the structural mean of a sample of curves by dynamic time warping	p. 39
Sequential decisional discriminant analysis	p. 49
Regularized sliced inverse regression with applications in classification	p. 59
Approaches to asymmetric multidimensional scaling with external information	p. 69
Variable architecture Bayesian neural networks : model selection based on EMC	p. 77
Missing data in optimal scaling	p. 85
Simple component analysis based on RV coefficient	p. 93
Baum-Eagon inequality in probabilistic labeling problems	p. 103
Monotone constrained EM algorithms for multinormal mixture models	p. 111
Visualizing dependence of bootstrap confidence intervals for methods yielding spatial configurations	p. 119
Automatic discount selection for exponential family state-space models	p. 127
A generalization of the polychoric correlation coefficient	p. 135
The effects of MEP distributed random effects on variance component estimation in multilevel models	p. 143
Calibration confidence regions using empirical likelihood	p. 153
Random start forward searches with envelopes for detecting clusters in multivariate data	p. 163
Robust transformation of proportions using the forward search	p. 173
The forward search method applied to geodetic transformations	p. 181
An R package for the forward analysis of multivariate data	p. 189
A forward search method for robust generalised procrustes analysis	p. 199
A projection method for robust estimation and clustering in large data sets	p. 209
Robust multivariate calibration	p. 217
Procrustes techniques for text mining	p. 227
Building recommendations from random walks on library OPAC usage data	p. 235
A software tool via Web for the statistical data analysis : R-php	p. 247
Evolutionary algorithms for classification and regression trees	p. 255
Variable selection using random forests	p. 263
Boosted incremental tree-based imputation of missing data	p. 271
Sensitivity of attributes on the performance of attribute-aware collaborative filtering	p. 279
Customer satisfaction evaluation : an approach based on simultaneous diagonalization	p. 289
Analyzing evaluation data : modelling and testing for homogeneity	p. 299
Archetypal analysis for data driven benchmarking	p. 309
Determinants of secondary school dropping out : a structural equation model	p. 319
Testing procedures for multilevel models with administrative data	p. 329
Multidimensional versus unidimensional models for ability testing	p. 339
A spatial mixed model for sectorial labour market data	p. 349
The impact of the new labour force survey on the employed classification	p. 359
Using CATPCA to evaluate market regulation	p. 369
Credit risk management through robust generalized linear models	p. 377
Classification of financial returns according to thresholds exceedances	p. 387
Nonparametric clustering of seismic events	p. 397
A non-homogeneous poisson based model for daily rainfall data	p. 405
A comparison of data mining methods and logistic regression to determine factors associated with death following injury	p. 417
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