R Under development (unstable) (2024-10-16 r87241 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(mbbefd)
Loading required package: fitdistrplus
Loading required package: MASS
Loading required package: survival
Loading required package: alabama
Loading required package: numDeriv
Loading required package: Rcpp
Package:  mbbefd
Version:  0.8.12
Date:     
BugReport: https://github.com/spedygiorgio/mbbefd/issues


> 
> #test of shifted truncated pareto distribution
> n <- 1e1
> 
> x <- rstpareto(n, 2)+0.01
> y <- rstpareto(n, 2)
> 
> #test CDF
> z <- 0:4/4
> ecdf(x)(z)
[1] 0.0 0.5 0.8 0.8 1.0
> 
> #test EC
> f <- function(d)
+   mean(pmin(x, d))/mean(x)
> rval <- Vectorize(f, "d")
> 
> cbind(eecf(x)(x), rval(x))
           [,1]      [,2]
 [1,] 1.0000000 1.0000000
 [2,] 0.9470364 0.9470364
 [3,] 0.5150777 0.5150777
 [4,] 0.6711407 0.6711407
 [5,] 0.1048102 0.1048102
 [6,] 0.7523371 0.7523371
 [7,] 0.1866845 0.1866845
 [8,] 0.2254057 0.2254057
 [9,] 0.6368639 0.6368639
[10,] 0.5318189 0.5318189
> cbind(eecf(x)(z), rval(z))
          [,1]      [,2]
[1,] 0.0000000 0.0000000
[2,] 0.5521161 0.5521161
[3,] 0.7924679 0.7924679
[4,] 0.9377673 0.9377673
[5,] 1.0000000 1.0000000
> 
> class(eecf(x))
[1] "eecf"     "function"
> class(ecdf(x))
[1] "ecdf"     "stepfun"  "function"
> 
> print(eecf(x))
Empirical Exposure Curve Function 
Call: eecf(x)
 x[1:10] = 0.036067, 0.067372, 0.084028,  ..., 0.76595, 0.94821
> print(ecdf(x))
Empirical CDF 
Call: ecdf(x)
 x[1:10] = 0.036067, 0.067372, 0.084028,  ..., 0.76595, 0.94821
> 
> cbind(eecf(x)(sort(x)), 
+ environment(eecf(x))$"Gx")
           [,1]      [,2]
 [1,] 0.1048102 0.1048102
 [2,] 0.1866845 0.1866845
 [3,] 0.2254057 0.2254057
 [4,] 0.5150777 0.5150777
 [5,] 0.5318189 0.5318189
 [6,] 0.6368639 0.6368639
 [7,] 0.6711407 0.6711407
 [8,] 0.7523371 0.7523371
 [9,] 0.9470364 0.9470364
[10,] 1.0000000 1.0000000
> 
> print(summary(eecf(x)))
Empirical Exposure Curve Function:    10 unique values with summary
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.03607 0.11960 0.27220 0.34410 0.40770 0.94820 
> print(summary(ecdf(x)))
Empirical CDF:	  10 unique values with summary
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
0.03607 0.11963 0.27218 0.34412 0.40767 0.94821 
> 
> plot(eecf(x))
> plot(ecdf(x))
> 
> 
> plot(eecf(x))
> plot(eecf(y), add=TRUE, col="red")
> lines(eecf(y[1:5]), col="green")
> 
> ?plot.eecf
> ?summary.eecf
> 
> proc.time()
   user  system elapsed 
   1.96    0.40    2.36