fuzzysum {fuzzyOP} | R Documentation |
The sum of fuzzy numbers is computed and, if required, the fuzzy numbers are plotted.
fuzzysum(anz, A , vektor, pl)
anz |
Number of the delta-cuts. |
A |
Dataset, which must have at least 2 columns. |
vektor |
Vector, that describes which fuzzy numbers from the dataset are selected. |
pl |
Plot-option, 0 or 1 or 2 |
For more information about the necessary data format see: test
The sum of the fuzzy numbers is computed, and if the plot-option is set to 1,
the characterizing function of the sum is depicted. If the option 2 is selected, then
the characterizing functions of the fuzzy numbers are plotted in one plot and the
characterizing function of the sum in another one.
If the plot-option is set to 0, then no plot is produced.
Output data is of the same type as input data.
Therefore the returned value is a matrix containing the sum of fuzzy numbers, which is again
a piecewise linear fuzzy number.
The first column describes the x-values and
the second one the values of the characterizing function
of the supporting points of the sum of the fuzzy numbers.
Semagül Aklan, Emine Altindas, Yi Hong Kang, Rabiye Macit, Senay Umar, Hatice Ünal
R. Viertl, D. Hareter: Beschreibung und Analyse unscharfer Information - Statistische Methoden für unscharfe Daten, Springer, Wien, 2006
fuzzynumber
, fuzzymin
, fuzzymax
, fuzzydeltacut
, fuzzymean
, fuzzyscalar
, fuzzyproduct
, fuzzypower
, fuzzyfunction
require(fuzzyOP) ##Example 1: ##create data: a<-c(-1,0,1,NA,NA,NA) b<-c(0,1,0,NA,NA,NA) d<-c(1,2,3,4,5,6) e<-c(0,0.3,1,0.4,0.2,0) f<-c(1:5,NA) g<-c(0,0.2,1,0.5,0,NA) B<-cbind(a,b,d,e,f,g) ##execute: fuzzysum(100,B,c(1,2),2) ##Example 2: data(test) A<-fuzzysum(5,test,c(1,4,8),1) A