Applied Multivariate Statistical Analysis - UFPR

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Applied MultivariateStatistical Analysis Wolfgang H ardleL eopold Simar Version: 29th April 2003ContentsIDescriptive Techniques111 Comparison of Boxplots. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Histograms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Kernel Densities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Scatterplots. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chernoff-Flury Faces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andrews Curves.

cluster analysis deals with the various cluster techniques and leads naturally to the problem of discrimination analysis. The next chapter deals with the detection of correspondence between factors. The joint structure of data sets is presented in the chapter on canonical

  Analysis, Chapter, Statistical, Applied, Cluster, Multivariate, Applied multivariate statistical analysis