fastJT
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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.8 |
rolling source/ R- | fastJT_1.0.8.tar.gz |
290.0 KiB |
1.0.8 |
latest source/ R- | fastJT_1.0.8.tar.gz |
290.0 KiB |
1.0.8 |
2026-04-23 source/ R- | fastJT_1.0.8.tar.gz |
290.0 KiB |
1.0.8 |
2026-04-09 windows/windows R-4.5 | fastJT_1.0.8.zip |
785.8 KiB |