Titlebook: Injuries and Health Problems in Football; What Everyone Should João Espregueira-Mendes (Editor-in-chief),C. Niek Book 2017 Springer-Verlag

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ate normally distributed random variables generate couples of ordinal scores. Categories of the two ordinal variables correspond to intervals of the corresponding continuous variables. Thus, measuring the association between ordinal variables means estimating the product moment correlation between t

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he Italian Statistical Society, which was held in Parma, June 6-8, 2005. Sergio Zani chaired the Scientific Programme Committee and Andrea Cerioli chaired the Local Organizing Committee. The scientific programme of the conference included 127 papers, 42 in spe­ cialized sessions, 68 in contributed p

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José Ferraz,José Pereira,Jacques Menetrey,Paulo LoboADAG) of the Italian Statistical Society, which was held in Parma, June 6-8, 2005. Sergio Zani chaired the Scientific Programme Committee and Andrea Cerioli chaired the Local Organizing Committee. The scientific programme of the conference included 127 papers, 42 in spe­ cialized sessions, 68 in con

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Henrique Jones,Pedro Cantista,Matteo DentiADAG) of the Italian Statistical Society, which was held in Parma, June 6-8, 2005. Sergio Zani chaired the Scientific Programme Committee and Andrea Cerioli chaired the Local Organizing Committee. The scientific programme of the conference included 127 papers, 42 in spe­ cialized sessions, 68 in con

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2000. ISBN 1-58025-660-0; Meyer et al., J. Stat. Softw., 2006; Meyer et al., vcd: Visualizing Categorical Data. R package version 1.0.9, 2008). Graphical methods for qualitative data and extension using a variety of R packages will be presented. This paper outlines a general framework for visual mod

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Rogério Pereira,Ricardo Vidal,Ana Leal,Maria Amélia Ferreiral cost due to the cubic runtime complexity is problematic for larger data sets. To mitigate this, Graf et al. (Adv. Neural Inf. Process. Syst. 17:521–528, 2005) proposed the Cascade SVM. It is a simple, stepwise procedure, in which the SVM is iteratively trained on subsets of the original data set a