Computed ABC Analysis

For a given data set, the package provides a novel method of computing precise limits to acquire subsets which are easily interpreted. Closely related to the Lorenz curve, the ABC curve visualizes the data by graphically representing the cumulative distribution function. Based on an ABC analysis the algorithm calculates, with the help of the ABC curve, the optimal limits by exploiting the mathematical properties pertaining to distribution of analyzed items. The data containing positive values is divided into three disjoint subsets A, B and C, with subset A comprising very profitable values, i.e. largest data values ("the important few"), subset B comprising values where the yield equals to the effort required to obtain it, and the subset C comprising of non-profitable values, i.e., the smallest data sets ("the trivial many"). Package is based on "Computed ABC Analysis for rational Selection of most informative Variables in multivariate Data", PLoS One. Ultsch. A., Lotsch J. (2015) .


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install.packages("ABCanalysis")

1.2.1 by Florian Lerch, 7 months ago


https://www.uni-marburg.de/fb12/datenbionik/software-en


Browse source code at https://github.com/cran/ABCanalysis


Authors: Michael Thrun, Jorn Lotsch, Alfred Ultsch


Documentation:   PDF Manual  


GPL-3 license


Imports plotrix


Suggested by DatabionicSwarm.


See at CRAN