incorrect results from empirical_cdf? #18
Description
Hello!
I'm getting unexpected results from mltools::empirical_cdf() that differ from a base R implementation as well as the Emcdf::emcdf() implementation. Am I missing something that would make the {mltools} implementation correct and the other ones wrong?
Here's a reproducible example:
library(data.table)
library(mltools)
library(Emcdf)
library(purrr)
set.seed(1235)
(data <- as.matrix(data.frame(x = rnorm(n = 5), y = rnorm(n = 5), z = rnorm(n = 5))))
The data look like this:
x y z
[1,] -0.6979879 1.69819652 -0.9403661
[2,] -1.2848539 0.04784562 1.0849639
[3,] 0.9899590 0.65486241 -0.7501569
[4,] 0.1117758 1.36528367 -0.4216928
[5,] 0.1142077 0.40257296 -0.8231759
And the implementation of the ecdf looks like this:
dt <- data.table(data)
obj <- initF(data, 2)
(base_R <- pmap_dbl(dt, .f = function(x, y, z) {
mean(data[, "x"] <= x & data[, "y"] <= y & data[, "z"] <= z)
}))
(Emcdf_package <- emcdf(obj, data))
(mltools_package <- empirical_cdf(dt, ubounds = dt)$CDF)
(results <- data.frame(base_R, Emcdf_package, mltools_package))
Which yields:
base_R Emcdf_package mltools_package
1 0.2 0.2 0.2
2 0.2 0.2 0.2
3 0.4 0.4 0.2
4 0.2 0.2 0.2
5 0.2 0.2 0.2