Advances in Multivariate Data Analysis: Proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Palermo, July 5 - 6, 2001 ; with 56 Tables
Springer Science & Business Media, Apr 20, 2004 - Business & Economics - 281 pages
This volume contains a selection of papers presented during the biennial meeting of the CLAssification and Data Analysis Group (CLADAG) of the Societa Italiana di Statistica which was orga nized by the Istituto di Statistica of the Universita degli Studi di Palermo and held in the Palazzo Steri in Palermo on July 5-6, 2001. For this conference, and after checking the submitted 4 page abstracts, 54 papers were admitted for presentation. They covered a large range of topics from multivariate data analysis, with special emphasis on classification and clustering, computa tional statistics, time series analysis, and applications in various classical or recent domains. A two-fold careful reviewing process led to the selection of 22 papers which are presented in this vol ume. They convey either a new idea or methodology, present a new algorithm, or concern an interesting application. We have clustered these papers into five groups as follows: 1. Classification Methods with Applications 2. Time Series Analysis and Related Methods 3. Computer Intensive Techniques and Algorithms 4. Classification and Data Analysis in Economics 5. Multivariate Analysis in Applied Sciences. In each section the papers are arranged in alphabetical order. The editors - two of them the organizers of the CLADAG confer ence - would like to express their gratitude to the authors whose enthusiastic participation made the meeting possible and very successful.
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algorithm application approach autoregressive basis function Bayes factor Bayesian bootstrap box plots Breiman CART classification trees cluster Co-Structure coefficients component computed considered covariates criterion Data Analysis data set defined Dipartimento dissimilarity domain dynamic eigenvectors equation error rate evaluate expert explanatory variables frequency fuzzy Gaussian GMRF heterogeneity heteroskedasticity homoskedastic household interaction ISTAT Italy k-means k-medoids Kalman filter likelihood function Machine Learning matrix maximum likelihood mean measure methods Monte Carlo multivariate neural network noise observations obtained optimal ordinal overfitting paper Parametric estimation performance periodogram posterior poverty predictor problem procedure proposed pruning random regression model relevant represented respect response variable Scienze scoring Section selection signal simulation smoother smoothing species split standard errors stationary process Statistica Statistical structure Symbolic Data symmetric Table threshold timated tion transition UniversitÓ values wavelet weights wholesale trade zero