R Under development (unstable) (2025-11-06 r88990 ucrt) -- "Unsuffered Consequences"
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> 
>  library(fuzzyRankTests)
> 
>  options(digits=5) # avoid rounding differences
> 
>  x <- c(1, 2, 3, 4, 4, 4, 5, 6, 7)
>  y <- c(4, 5, 7, 7, 8, 9, 10, 11)
> 
>  fuzzy.ranksum.test(x, y)

	Mann-Whitney-Wilcoxon rank sum test

data:  x and y 
alternative hypothesis: true mu is not equal to 0 

fuzzy P-value has continuous, piecewise linear CDF with knots and
values

     knots  values
 0.0009872 0.00000
 0.0015631 0.04167
 0.0024681 0.16667
 0.0037022 0.37500
 0.0055121 0.62500
 0.0078980 0.83333
 0.0111065 0.95833
 0.0152201 1.00000

> 
>  wilcox.test(x, y, exact = FALSE)

	Wilcoxon rank sum test with continuity correction

data:  x and y
W = 8, p-value = 0.0076
alternative hypothesis: true location shift is not equal to 0

> 
>  fuzzy.ranksum.test(x, y, alt = "less")

	Mann-Whitney-Wilcoxon rank sum test

data:  x and y 
alternative hypothesis: true mu is less than 0 

fuzzy P-value has continuous, piecewise linear CDF with knots and
values

     knots  values
 0.0004936 0.00000
 0.0007816 0.04167
 0.0012341 0.16667
 0.0018511 0.37500
 0.0027561 0.62500
 0.0039490 0.83333
 0.0055533 0.95833
 0.0076100 1.00000

> 
>  wilcox.test(x, y, alt = "less", exact = FALSE)

	Wilcoxon rank sum test with continuity correction

data:  x and y
W = 8, p-value = 0.0038
alternative hypothesis: true location shift is less than 0

> 
>  fuzzy.ranksum.ci(x, y)

	Mann-Whitney-Wilcoxon rank sum test

data:  x and y 
95 percent confidence interval:

Fuzzy confidence interval:

        set  value
 (-Inf, -6) 0.0000
       {-6} 0.5503
   (-6, -1) 1.0000
       {-1} 0.2241
  (-1, Inf) 0.0000


> 
>  wilcox.test(x, y, conf.int = TRUE, exact = FALSE)

	Wilcoxon rank sum test with continuity correction

data:  x and y
W = 8, p-value = 0.0076
alternative hypothesis: true location shift is not equal to 0
95 percent confidence interval:
 -6.0001 -1.0001
sample estimates:
difference in location 
                    -4 

> 
>  fuzzy.ranksum.ci(x, y, alt = "less")

	Mann-Whitney-Wilcoxon rank sum test

data:  x and y 
95 percent confidence interval:

Fuzzy confidence interval:

        set  value
 (-Inf, -2) 1.0000
       {-2} 0.9434
  (-2, Inf) 0.0000


> 
>  wilcox.test(x, y, conf.int = TRUE, alt = "less", exact = FALSE)

	Wilcoxon rank sum test with continuity correction

data:  x and y
W = 8, p-value = 0.0038
alternative hypothesis: true location shift is less than 0
95 percent confidence interval:
 -Inf   -2
sample estimates:
difference in location 
                    -4 

> 
>  fuzzy.ranksum.ci(x, y, alt = "great")

	Mann-Whitney-Wilcoxon rank sum test

data:  x and y 
95 percent confidence interval:

Fuzzy confidence interval:

        set   value
 (-Inf, -6) 0.00000
       {-6} 0.04463
  (-6, Inf) 1.00000


> 
>  wilcox.test(x, y, conf.int = TRUE, alt = "great", exact = FALSE)

	Wilcoxon rank sum test with continuity correction

data:  x and y
W = 8, p-value = 1
alternative hypothesis: true location shift is greater than 0
95 percent confidence interval:
  -6 Inf
sample estimates:
difference in location 
                    -4 

> 
> 
> proc.time()
   user  system elapsed 
   0.15    0.06    0.20