Title: | Single Valued Neutrosophic Kruskal-Wallis and Mann Whitney Tests |
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Description: | Dealing with neutrosophic data in single valued form using score, accuracy and certainty functions to calculate ranks of Single Valued Neutrosophic Set (SVNS), also to calculate the Mann-Whitney test, and making a post-hoc test after rejecting the null hypothesis using the Neutrosophic Statistics Kruskal-Wallis test. For more information see Miari, Mahmoud; Anan, Mohamad Taher; Zeina, Mohamed Bisher(2022) <https://digitalrepository.unm.edu/nss_journal/vol51/iss1/60/>. |
Authors: | Mohamad Taher Anan [aut, cre] , Mohamad Bisher Zeina [aut], Aya Khantomani [aut], Mahmoud Miari [aut] |
Maintainer: | Mohamad Taher Anan <[email protected]> |
License: | GPL-3 |
Version: | 0.0.1 |
Built: | 2024-11-19 06:35:24 UTC |
Source: | CRAN |
This function to calculate the kruskal test(with neutrosophic data)
fanan(dt)
fanan(dt)
dt |
ia a data frame |
kruskal test
fac=c(rep("1",6),rep("2",6),rep("3",4)) t=c(0.4,0.42,0.04,0.46,0.08,0.33,0.13,0.003,0.0095,0.44,0.003,0.62,0.15,0.498,0.36,0.464) i=c(0.06,0.071,0.5,0.14,0.03,0.30,0.45,0.074,0.17,0.28,0.48,0.072,0.62,0.148,0.831,0.761) f=c(0.46,0.37,0.21,0.31,0.171,0.21,0.39,0.083,0.41,0.42,0.31,0.18,0.29,0.748,0.625,0.551) dt=data.frame(t,i,f,fac) fanan(dt)
fac=c(rep("1",6),rep("2",6),rep("3",4)) t=c(0.4,0.42,0.04,0.46,0.08,0.33,0.13,0.003,0.0095,0.44,0.003,0.62,0.15,0.498,0.36,0.464) i=c(0.06,0.071,0.5,0.14,0.03,0.30,0.45,0.074,0.17,0.28,0.48,0.072,0.62,0.148,0.831,0.761) f=c(0.46,0.37,0.21,0.31,0.171,0.21,0.39,0.083,0.41,0.42,0.31,0.18,0.29,0.748,0.625,0.551) dt=data.frame(t,i,f,fac) fanan(dt)
SORTING DATA
s_sort(y1, y2, ac, ce, rw)
s_sort(y1, y2, ac, ce, rw)
y1 |
is a score variable |
y2 |
is a string variable but in numeric elements |
ac |
is an accuracy variable |
ce |
is a certainty variable |
rw |
rw is a number of rows in dt |
sorting Data
fac=c(rep("1",6),rep("2",6),rep("3",4)) t=c(0.4,0.42,0.04,0.46,0.08,0.33,0.13,0.003,0.0095,0.44,0.003,0.62,0.15,0.498,0.36,0.464) i=c(0.06,0.071,0.5,0.14,0.03,0.30,0.45,0.074,0.17,0.28,0.48,0.072,0.62,0.148,0.831,0.761) f=c(0.46,0.37,0.21,0.31,0.171,0.21,0.39,0.083,0.41,0.42,0.31,0.18,0.29,0.748,0.625,0.551) dt=data.frame(t,i,f,fac) sc=(2+dt[,1]-dt[,2]-dt[,3])/3 ac=dt[,1]-dt[,3] ce=dt[,1] y1=sc y1=round(y1,2) y2=as.character(dt[,4]) rw=nrow(dt) ff=s_sort(y1,y2,ac,ce,rw) ff=s_sort(ac,y2,y1,ce,rw) ff=s_sort(ce,y2,ac,y1,rw) ff=s_sort(y1,y2,ac,ce,rw) y1=ff$y1 y2=ff$y2 ac=ff$ac ce=ff$ce ff=data.frame(y1,y2,ac,ce) print(ff)
fac=c(rep("1",6),rep("2",6),rep("3",4)) t=c(0.4,0.42,0.04,0.46,0.08,0.33,0.13,0.003,0.0095,0.44,0.003,0.62,0.15,0.498,0.36,0.464) i=c(0.06,0.071,0.5,0.14,0.03,0.30,0.45,0.074,0.17,0.28,0.48,0.072,0.62,0.148,0.831,0.761) f=c(0.46,0.37,0.21,0.31,0.171,0.21,0.39,0.083,0.41,0.42,0.31,0.18,0.29,0.748,0.625,0.551) dt=data.frame(t,i,f,fac) sc=(2+dt[,1]-dt[,2]-dt[,3])/3 ac=dt[,1]-dt[,3] ce=dt[,1] y1=sc y1=round(y1,2) y2=as.character(dt[,4]) rw=nrow(dt) ff=s_sort(y1,y2,ac,ce,rw) ff=s_sort(ac,y2,y1,ce,rw) ff=s_sort(ce,y2,ac,y1,rw) ff=s_sort(y1,y2,ac,ce,rw) y1=ff$y1 y2=ff$y2 ac=ff$ac ce=ff$ce ff=data.frame(y1,y2,ac,ce) print(ff)