ABCanalysis-package {ABCanalysis}

Computed ABC analysis

Description

Computed ABC Analysis allows the optimal calculation of three disjoint subsets A,B,C in data sets containing positive values:

subset A containing few most profitable values, i.e. largest data values ("the important few"), subset B containing data, where the profit gain equals effort required to obtain this gain, and the subset C of non-profitable values, i.e. the smallest data sets ("the trivial many").

This package calculates the three subsets A, B and C by means of an algorithm based on statistically valid definitions of thresholds for the three sets A,B and C.

Note

Check out our new Umatrix package for visualisation and clustering of high-dimensional data on our Webpage.

Author(s)

Michael Thrun, Jorn Lotsch, Alfred Ultsch

http://www.uni-marburg.de/fb12/datenbionik

[e-mail]

References

Ultsch. A ., Lotsch J.: Computed ABC Analysis for Rational Selection of Most Informative Variables in Multivariate Data, PloS one, Vol. 10(6), pp. e0129767. doi 10.1371/journal.pone.0129767, 2015.

Examples

  data("SwissInhabitants")
	abc=ABCanalysis(SwissInhabitants,PlotIt=TRUE)
	SetA=SwissInhabitants[abc$Aind]
	SetB=SwissInhabitants[abc$Bind]
	SetC=SwissInhabitants[abc$Cind]