ABCanalysis-package: Computed ABC analysis
In Mthrun/ABCanalysis: Computed ABC Analysis

Description Note Author(s) References Examples

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.

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

Michael Thrun, Jorn Lotsch, Alfred Ultsch

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

mthrun@mathematik.uni-marburg.de

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.

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