The goal of rawKS is to easily extract the raw KS statistics to plot and report. The Python version pyks is hosted from GitHub.

You can install the released version of rawKS from CRAN with:

install.packages("rawKS")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("JiaxiangBU/rawKS")

This is a basic example which shows you how to solve a common problem:

library(rawKS)
#> Registered S3 methods overwritten by 'ggplot2':
#>   method         from 
#>   [.quosures     rlang
#>   c.quosures     rlang
#>   print.quosures rlang

data("two_class_example_edited")
max(ks_table(two_class_example_edited$yhat, two_class_example_edited$y)$ks)
#> [1] 0.7276892
ks_table(two_class_example_edited$yhat, two_class_example_edited$y) %>% 
  ks_plot()

Jiaxiang Li. (2020, February 8). JiaxiangBU/rawKS: rawKS 0.1.0 (Version v0.1.0). Zenodo. http://doi.org/10.5281/zenodo.3659683

@software{jiaxiang_li_2020_3659683,
  author       = {Jiaxiang Li},
  title        = {JiaxiangBU/rawKS: rawKS 0.1.0},
  month        = feb,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {v0.1.0},
  doi          = {10.5281/zenodo.3659683},
  url          = {https://doi.org/10.5281/zenodo.3659683}
}

If you use rawKS, I would be very grateful if you can add a citation in your published work. By citing rawKS, beyond acknowledging the work, you contribute to make it more visible and guarantee its growing and sustainability. For citation, please use the BibTex or the citation content.