Package: FunChisq
Type: Package
Title: Chi-Square and Exact Tests for Non-Parametric Functional
        Dependencies
Version: 2.3.1
Author: Yang Zhang, Hua Zhong, and Joe Song
Maintainer: Joe Song <joemsong@cs.nmsu.edu>
Description: Statistical hypothesis testing methods for non-parametric functional dependencies using asymptotic chi-square or exact statistics. These tests were motivated to reveal evidence for causality based on functional dependencies. They include asymptotic functional chi-square tests, an exact functional test, a comparative functional chi-square test, and also a comparative chi-square test. The normalized non-constant functional chi-square test was used by Best Performer NMSUSongLab in HPN-DREAM (DREAM8) Breast Cancer Network Inference Challenges. For continuous data, these tests offer an advantage over regression analysis when a parametric functional form cannot be assumed; for categorical data, they provide a novel means to assess directional dependencies impossible with classical Pearson's chi-square or Fisher's exact tests.
License: LGPL (>= 3)
Depends: R (>= 3.0.0)
Imports: Rcpp, stats
LinkingTo: BH, Rcpp
Suggests: Ckmeans.1d.dp, testthat, knitr, rmarkdown
NeedsCompilation: yes
URL: http://www.cs.nmsu.edu/~joemsong/publications
LazyData: TRUE
VignetteBuilder: knitr
Packaged: 2016-05-01 23:51:37 UTC; joemsong
Repository: CRAN
Date/Publication: 2016-05-02 06:24:25