Titlebook: Grade Models and Methods for Data Analysis; With Applications fo Teresa Kowalczyk,El?bieta Pleszczyńska,Frederick R Book 2004 Springer-Verl

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Regularity and the number of clusters, curves introduced in Chapter 6. It will be shown that members of a parametrized family of two-dimensional distributions from the Bivariate Lilliputian Model (???)which are based on parabolas are ideally regular data tables (Sections 11.2–11.3).

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Inequality measures for multivariate distributions,variate datasets with . sets of records. These measures are easy to percept for those who are familiar with the concepts of the Lorenz Curve and Gini Index which are so important in the univariate case.

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Univariate Lilliputian Model II,s, data were ordered according to increasing earnings. For earnings aggregated to four macrocategories, the concentration curve .(. : .) relating male earnings . to female earnings . happened to be convex. This indicated a clear monotone trend: the higher the earnings macrocategory, the stronger the

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Asymmetry and the inverse concentration set,ack sufficient precision. It is due to the fact that there are many curves which have the same index value. Problems related to how greatly such curves may differ are discussed in Sec. 5.2. In particular, the boundaries of the smallest region containing all maximal concentration curves with a common