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.
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.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(ABCanalysis)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ABCanalysis/ABCanalysis-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ABCanalysis-package
> ### Title: Computed ABC analysis
> ### Aliases: ABCanalysis-package ABCanalyse dbt.ABC dbt.ABCanalyse
> ### dbt.ABCanalysis
> ### Keywords: package
>
> ### ** Examples
>
> data("SwissInhabitants")
> abc=ABCanalysis(SwissInhabitants,PlotIt=TRUE)
> SetA=SwissInhabitants[abc$Aind]
> SetB=SwissInhabitants[abc$Bind]
> SetC=SwissInhabitants[abc$Cind]
>
>
>
>
>
> dev.off()
null device
1
>