Efficient Jonckheere-Terpstra Test Statistics for Robust Machine Learning and Genome-Wide Association Studies

This 'Rcpp'-based package implements highly efficient functions for the calculation of the Jonckheere-Terpstra statistic. It can be used for a variety of applications, including feature selection in machine learning problems, or to conduct genome-wide association studies (GWAS) with multiple quantitative phenotypes. The code leverages 'OpenMP' directives for multi-core computing to reduce overall processing time.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("fastJT")

1.0.8 by Alexander Sibley, a year ago


Browse source code at https://github.com/cran/fastJT


Authors: Jiaxing Lin [aut] , Alexander Sibley [aut, cre] , Ivo Shterev [aut] , Kouros Owzar [aut]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp

Suggests knitr

Linking to Rcpp


See at CRAN