COMPSTAT 2006 - Proceedings in Computational Statistics [electronic resource] : 17th Symposium Held in Rome, Italy, 2006 /
Symposium on Computational StatisticsCorporate Author
Symposium on Computational Statistics(17th :2006 :Rome, Italy)
Symposium on Computational Statistics
International Association for Statistical Computing.
Rizzi, Alfredo.editor.
Vichi, Maurizio.editor.
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).
Description based upon print version of record.
Includes bibliographical references and index.
Classification and Clustering -- Issues of robustness and high dimensionality in cluster analysis -- Fuzzy K-medoids clustering models for fuzzy multivariate time trajectories -- Bootstrap methods for measuring classification uncertainty in latent class analysis -- A robust linear grouping algorithm -- Computing and using the deviance with classification trees -- Estimation procedures for the false discovery rate: a systematic comparison for microarray data -- A unifying model for biclustering -- Image Analysis and Signal Processing -- Non-rigid image registration using mutual information -- Musical audio analysis using sparse representations -- Robust correspondence recognition for computer vision -- Blind superresolution -- Analysis of Music Time Series -- Data Visualization -- Tying up the loose ends in simple, multiple, joint correspondence analysis -- 3 dimensional parallel coordinates plot and its use for variable selection -- Geospatial distribution of alcohol-related violence in Northern Virginia -- Visualization in comparative music research -- Exploratory modelling analysis: visualizing the value of variables -- Density estimation from streaming data using wavelets -- Multivariate Analysis -- Reducing conservatism of exact small-sample methods of inference for discrete data -- Symbolic data analysis: what is it? -- A dimensional reduction method for ordinal three-way contingency table -- Operator related to a data matrix: a survey -- Factor interval data analysis and its application -- Identifying excessively rounded or truncated data -- Statistical inference and data mining: false discoveries control -- Is 'Which model . . .?' the right question? -- Use of latent class regression models with a random intercept to remove the effects of the overall response rating level -- Discrete functional data analysis -- Self organizing MAPS: understanding, measuring and reducing variability -- Parameterization and estimation of path models for categorical data -- Latent class model with two latent variables for analysis of count data -- Web Based Teaching -- Challenges concerning web data mining -- e-Learning statistics - a selective review -- Quality assurance of web based e-Learning for statistical education -- Algorithms -- Genetic algorithms for building double threshold generalized autoregressive conditional heteroscedastic models of time series -- Nonparametric evaluation of matching noise -- Subset selection algorithm based on mutual information -- Visiting near-optimal solutions using local search algorithms -- The convergence of optimization based GARCH estimators: theory and application -- The stochastics of threshold accepting: analysis of an application to the uniform design problem -- Robustness -- Robust classification with categorical variables -- Multiple group linear discriminant analysis: robustness and error rate.
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).
Probabilities.
Computer software.
Database management.
Statistics .
Information storage and retrieval.
Mathematical statistics.
Probability Theory and Stochastic Processes.
Mathematical Software.
Database Management.
Statistics and Computing/Statistics Programs.
Information Storage and Retrieval.
Probability and Statistics in Computer Science.