By Carmela Cappelli, Francesco Mola (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Marcello Chiodi, Prof. Antonino Mineo (eds.)
This quantity features a choice of papers provided through the biennial assembly of the category and information research team (CLADAG) of the Societa Italiana di Statistica which used to be orga nized via the Istituto di Statistica of the Universita degli Studi di Palermo and held within the Palazzo Steri in Palermo on July 5-6, 2001. For this convention, and after checking the submitted four web page abstracts, fifty four papers have been admitted for presentation. They coated a wide range of subject matters from multivariate info research, with particular emphasis on type and clustering, computa tional information, time sequence research, and functions in a number of classical or contemporary domain names. A two-fold cautious reviewing procedure ended in the choice of twenty-two papers that are provided during this vol ume. they communicate both a brand new notion or technique, current a brand new set of rules, or challenge an engaging software. we've got clustered those papers into 5 teams as follows: 1. type equipment with purposes 2. Time sequence research and similar equipment three. machine extensive strategies and Algorithms four. type and knowledge research in Economics five. Multivariate research in technologies. In every one part the papers are prepared in alphabetical order. The editors - of them the organizers of the CLADAG confer ence - want to convey their gratitude to the authors whose enthusiastic participation made the assembly attainable and intensely successful.
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Additional resources for 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
H , k = 1, .. , K, where mhk is the number of objects which belong both to the h-th leaf of T; and to the k- th leaf of Tj . In analogy with a measure defined in Fowlkes and Mallows (1983) for the comparison of two hierarchical clusterings, a numerical measure of the degree of similarity between the two trees is then defined to be '\"' H B .. k=l m hk - n JPiQj , ZJ - (1) where K mhO H H K = Lmhk;mOk = Lmhk;Pi = Lm~o-n;Qj = L k=l h=l h=l m6k- n. k=l The B i j value is bounded between 0 and 1.
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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 by Carmela Cappelli, Francesco Mola (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Marcello Chiodi, Prof. Antonino Mineo (eds.)