fuzzyfunction {fuzzyOP} | R Documentation |
A continuous function will be applied to fuzzy numbers.
fuzzyfunction(f, anz, A, vektor, pl)
f |
A continuous function. |
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
If the plot-option is set to 1 the images of the fuzzy numbers under the function f
are calculated (via extension principle) and depicted. If the option 2 is selected, then
the characterizing functions of fuzzy numbers are plotted in one plot and
the characterizing function of the images 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. The returned value is a matrix containing the images of the function f applied to the fuzzy numbers. The odd columns contain the x-values and the even columns the values of the characterizing function of the supporting points of the fuzzy numbers under the function f.
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
, fuzzysum
, fuzzymean
, fuzzyscalar
, fuzzyproduct
, fuzzypower
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: fuzzyfunction(function(x){x+10},100,B,1,2) ##Example 2: data(test) A<-fuzzyfunction(sin,5,test,c(1,4,8),1) A