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) <DOI:10.1371/journal.pone.0129767>.
|Author||Michael Thrun, Jorn Lotsch, Alfred Ultsch|
|Date of publication||2017-03-13 14:31:38|
|Maintainer||Florian Lerch <email@example.com>|
ABCanalysis: Computed ABC analysis: calculates a division of the data in 3...
ABCanalysis4curve: calculate ABC Analysis from a given curve.
ABCanalysis-package: Computed ABC analysis
ABCanalysisPlot: Displays ABC plot with ABCanalysis
ABCcleanData: Data cleaning for ABC analysis
ABCcurve: calculates ABC Curve
ABCplot: displays an ABC Curve as an alternative to an Lorenz curve
ABCRemoveSmallYields: Extended Data cleaning for ABC analysis
calculatedABCanalysis: Computed ABC analysis: calculates a division of the data in 3...
Gini4ABC: Gini index
SwissInhabitants: SwissInhabitants in 1900
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