Package: fastJT 1.0.6

Alexander Sibley

fastJT: Efficient Jonckheere-Terpstra Test Statistics

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.

Authors:Jiaxing Lin, Alexander Sibley, Ivo Shterev, and Kouros Owzar

fastJT_1.0.6.tar.gz
fastJT_1.0.6.tar.gz(r-4.5-noble)fastJT_1.0.6.tar.gz(r-4.4-noble)
fastJT_1.0.6.tgz(r-4.4-emscripten)fastJT_1.0.6.tgz(r-4.3-emscripten)
fastJT.pdf |fastJT.html
fastJT/json (API)
NEWS

# Install 'fastJT' in R:
install.packages('fastJT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 8 scripts 274 downloads 1 mentions 4 exports 1 dependencies

Last updated 4 years agofrom:87afccc5ca. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-linux-x86_64NOTENov 21 2024

Exports:fastJTfastJT.selectpvaluessummary.fastJT

Dependencies:Rcpp

fastJT

Rendered fromfastJT.Rnwusingknitr::knitron Nov 21 2024.

Last update: 2020-11-10
Started: 2017-01-27