Advances in Multivariate Data Analysis: Proceedings of the by Carmela Cappelli, Francesco Mola (auth.), Prof. Dr.

Posted by

By Carmela Cappelli, Francesco Mola (auth.), Prof. Dr. Hans-Hermann Bock, Prof. Marcello Chiodi, Prof. Antonino Mineo (eds.)

This quantity includes a choice of papers offered throughout the biennial assembly of the category and information research team (CLADAG) of the Societa Italiana di Statistica which was once orga­ nized through 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 lined a wide variety of themes from multivariate info research, with targeted emphasis on class and clustering, computa­ tional facts, time sequence research, and functions in numerous classical or contemporary domain names. A two-fold cautious reviewing strategy resulted in the choice of twenty-two papers that are provided during this vol­ ume. they communicate both a brand new proposal or technique, current a brand new set of rules, or predicament an engaging software. now we have clustered those papers into 5 teams as follows: 1. type tools with functions 2. Time sequence research and comparable tools three. computing device in depth innovations and Algorithms four. category and information research in Economics five. Multivariate research in technologies. In each one part the papers are prepared in alphabetical order. The editors - of them the organizers of the CLADAG confer­ ence - want to show their gratitude to the authors whose enthusiastic participation made the assembly attainable and intensely successful.

Show description

Read Online or Download 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 PDF

Best analysis books

Functional analysis: proceedings of the Essen conference

Those complaints from the Symposium on useful research discover advances within the often separate parts of semigroups of operators and evolution equations, geometry of Banach areas and operator beliefs, and Frechet areas with functions in partial differential equations.

WiMAX: Technologies, Performance Analysis, and QoS (Wimax Handbook)

Because the call for for broadband prone maintains to develop all over the world, conventional options, resembling electronic cable and fiber optics, are frequently tough and dear to enforce, particularly in rural and distant components. The rising WiMAX method satisfies the starting to be want for top data-rate purposes resembling voiceover IP, video conferencing, interactive gaming, and multimedia streaming.

Extra info 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

Example text

Space Time Noisy Observation Smoothing 61 However it can be greatly facilitated by the adoption of the following stepwise optimisation procedure: 1. e. taking the OLS estimates of the regression of X on D; given the deterministic nature of D the OLS estimators are consistent and thus provide a valid and easily computed starting point; fio = D~o is substituted for fi in (14) and this is maximized through an iterative search algorithm (the Newton-Raphson iterative procedure has been successfully implemented to this purpose) to yield the est~ates ¢;o of 1>; 3.

The framework is the well known CART methodology (Breiman et al. (1984)) , which is actually the benchmark for the case when the response is nominal or numerical. Our criterion is obtained by measuring impurity within a node referring to a general measure of mutual dispersion (Gini (1954)) , which can be applied to every variable, whatever its nature. We show that the two measures of impurity at the basis of CART in the case when the response is nominal or quantitative can be obtained as particular cases of the above mentioned measure.

We also propose a new dissimilarity measure which overcomes some of the limitations highlighted. 36 Miglio and Soffritti Fig. 1. Boxplots of the proposed measure distributions (constant weights) . Similarly to some measures of partition correspondence, each proximity measure between classification trees should also be corrected for chance (Hubert and Arabie (1985)) so as to take on some constant value under an appropriate null model. : regression trees, survival trees). We are also studying algorithms, based on the proposed measure, suitable for identifying a consensus tree which summarizes the information contained in different trees.

Download PDF sample

Rated 4.60 of 5 – based on 14 votes