Ebook: Compstat 2006 - Proceedings in Computational Statistics: 17th Symposium Held in Rome, Italy, 2006

International Association for Statistical Computing The International Association for Statistical Computing (IASC) is a Section of the International Statistical Institute. The objectives of the Association are to foster world-wide interest in e?ective statistical computing and to - change technical knowledge through international contacts and meetings - tween statisticians, computing professionals, organizations, institutions, g- ernments and the general public. The IASC organises its own Conferences, IASC World Conferences, and COMPSTAT in Europe. The 17th Conference of ERS-IASC, the biennial meeting of European - gional Section of the IASC was held in Rome August 28 - September 1, 2006. This conference took place in Rome exactly 20 years after the 7th COMP- STAT symposium which was held in Rome, in 1986. Previous COMPSTAT conferences were held in: Vienna (Austria, 1974); West-Berlin (Germany, 1976); Leiden (The Netherlands, 1978); Edimbourgh (UK, 1980); Toulouse (France, 1982); Prague (Czechoslovakia, 1984); Rome (Italy, 1986); Copenhagen (Denmark, 1988); Dubrovnik (Yugoslavia, 1990); Neuchˆ atel (Switzerland, 1992); Vienna (Austria,1994); Barcelona (Spain, 1996);Bristol(UK,1998);Utrecht(TheNetherlands,2000);Berlin(Germany, 2002); Prague (Czech Republic, 2004).

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The book provides new developments in data analysis and statistical multivariate methods, computational statistics and algorithms, including new topics which are of central interest to modern statistics. The reader will find advanced methodologies and computational methods which are very helpful to analyze real phenomena characterized by large data bases. Furthermore, the volume includes papers devoted to original and innovative applications of recent statistical theory and complex approaches of statistical data analysis.

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The book provides new developments in data analysis and statistical multivariate methods, computational statistics and algorithms, including new topics which are of central interest to modern statistics. The reader will find advanced methodologies and computational methods which are very helpful to analyze real phenomena characterized by large data bases. Furthermore, the volume includes papers devoted to original and innovative applications of recent statistical theory and complex approaches of statistical data analysis.

Content:
Front Matter....Pages I-XXV
Front Matter....Pages 1-1
Issues of robustness and high dimensionality in cluster analysis....Pages 3-15
Fuzzy K-medoids clustering models for fuzzy multivariate time trajectories....Pages 17-29
Bootstrap methods for measuring classification uncertainty in latent class analysis....Pages 31-41
A robust linear grouping algorithm....Pages 43-53
Computing and using the deviance with classification trees....Pages 55-66
Estimation procedures for the false discovery rate: a systematic comparison for microarray data....Pages 67-79
A unifying model for biclustering....Pages 81-88
Front Matter....Pages 89-89
Non-rigid image registration using mutual information....Pages 91-103
Musical audio analysis using sparse representations....Pages 105-117
Robust correspondence recognition for computer vision....Pages 119-131
Blind superresolution....Pages 133-145
Analysis of Music Time Series....Pages 147-159
Front Matter....Pages 161-161
Tying up the loose ends in simple, multiple, joint correspondence analysis....Pages 163-185
3 dimensional parallel coordinates plot and its use for variable selection....Pages 187-195
Geospatial distribution of alcohol-related violence in Northern Virginia....Pages 197-207
Visualization in comparative music research....Pages 209-219
Exploratory modelling analysis: visualizing the value of variables....Pages 221-230
Density estimation from streaming data using wavelets....Pages 231-242
Front Matter....Pages 243-243
Reducing conservatism of exact small-sample methods of inference for discrete data....Pages 245-260
Symbolic data analysis: what is it?....Pages 261-269
Front Matter....Pages 243-243
A dimensional reduction method for ordinal three-way contingency table....Pages 271-283
Operator related to a data matrix: a survey....Pages 285-297
Factor interval data analysis and its application....Pages 299-312
Identifying excessively rounded or truncated data....Pages 313-323
Statistical inference and data mining: false discoveries control....Pages 325-336
Is ‘Which model . . .?’ the right question?....Pages 337-349
Use of latent class regression models with a random intercept to remove the effects of the overall response rating level....Pages 351-360
Discrete functional data analysis....Pages 361-369
Self organizing MAPS: understanding, measuring and reducing variability....Pages 371-382
Parameterization and estimation of path models for categorical data....Pages 383-394
Latent class model with two latent variables for analysis of count data....Pages 395-399
Front Matter....Pages 401-401
Challenges concerning web data mining....Pages 403-416
e-Learning statistics — a selective review....Pages 417-428
Quality assurance of web based e-Learning for statistical education....Pages 429-438
Front Matter....Pages 439-439
Genetic algorithms for building double threshold generalized autoregressive conditional heteroscedastic models of time series....Pages 441-452
Nonparametric evaluation of matching noise....Pages 453-460
Subset selection algorithm based on mutual information....Pages 461-470
Visiting near-optimal solutions using local search algorithms....Pages 471-481
The convergence of optimization based GARCH estimators: theory and application....Pages 483-494
The stochastics of threshold accepting: analysis of an application to the uniform design problem....Pages 495-503
Front Matter....Pages 505-505
Robust classification with categorical variables....Pages 507-519
Multiple group linear discriminant analysis: robustness and error rate....Pages 521-532
Back Matter....Pages 533-537

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The book provides new developments in data analysis and statistical multivariate methods, computational statistics and algorithms, including new topics which are of central interest to modern statistics. The reader will find advanced methodologies and computational methods which are very helpful to analyze real phenomena characterized by large data bases. Furthermore, the volume includes papers devoted to original and innovative applications of recent statistical theory and complex approaches of statistical data analysis.

Content:
Front Matter....Pages I-XXV
Front Matter....Pages 1-1
Issues of robustness and high dimensionality in cluster analysis....Pages 3-15
Fuzzy K-medoids clustering models for fuzzy multivariate time trajectories....Pages 17-29
Bootstrap methods for measuring classification uncertainty in latent class analysis....Pages 31-41
A robust linear grouping algorithm....Pages 43-53
Computing and using the deviance with classification trees....Pages 55-66
Estimation procedures for the false discovery rate: a systematic comparison for microarray data....Pages 67-79
A unifying model for biclustering....Pages 81-88
Front Matter....Pages 89-89
Non-rigid image registration using mutual information....Pages 91-103
Musical audio analysis using sparse representations....Pages 105-117
Robust correspondence recognition for computer vision....Pages 119-131
Blind superresolution....Pages 133-145
Analysis of Music Time Series....Pages 147-159
Front Matter....Pages 161-161
Tying up the loose ends in simple, multiple, joint correspondence analysis....Pages 163-185
3 dimensional parallel coordinates plot and its use for variable selection....Pages 187-195
Geospatial distribution of alcohol-related violence in Northern Virginia....Pages 197-207
Visualization in comparative music research....Pages 209-219
Exploratory modelling analysis: visualizing the value of variables....Pages 221-230
Density estimation from streaming data using wavelets....Pages 231-242
Front Matter....Pages 243-243
Reducing conservatism of exact small-sample methods of inference for discrete data....Pages 245-260
Symbolic data analysis: what is it?....Pages 261-269
Front Matter....Pages 243-243
A dimensional reduction method for ordinal three-way contingency table....Pages 271-283
Operator related to a data matrix: a survey....Pages 285-297
Factor interval data analysis and its application....Pages 299-312
Identifying excessively rounded or truncated data....Pages 313-323
Statistical inference and data mining: false discoveries control....Pages 325-336
Is ‘Which model . . .?’ the right question?....Pages 337-349
Use of latent class regression models with a random intercept to remove the effects of the overall response rating level....Pages 351-360
Discrete functional data analysis....Pages 361-369
Self organizing MAPS: understanding, measuring and reducing variability....Pages 371-382
Parameterization and estimation of path models for categorical data....Pages 383-394
Latent class model with two latent variables for analysis of count data....Pages 395-399
Front Matter....Pages 401-401
Challenges concerning web data mining....Pages 403-416
e-Learning statistics — a selective review....Pages 417-428
Quality assurance of web based e-Learning for statistical education....Pages 429-438
Front Matter....Pages 439-439
Genetic algorithms for building double threshold generalized autoregressive conditional heteroscedastic models of time series....Pages 441-452
Nonparametric evaluation of matching noise....Pages 453-460
Subset selection algorithm based on mutual information....Pages 461-470
Visiting near-optimal solutions using local search algorithms....Pages 471-481
The convergence of optimization based GARCH estimators: theory and application....Pages 483-494
The stochastics of threshold accepting: analysis of an application to the uniform design problem....Pages 495-503
Front Matter....Pages 505-505
Robust classification with categorical variables....Pages 507-519
Multiple group linear discriminant analysis: robustness and error rate....Pages 521-532
Back Matter....Pages 533-537
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