Statistical hypothesis testing methods for model-free functional dependency using asymptotic chi-square or exact distributions. Functional chi-squares are asymmetric and functionally optimal, unique from other related statistics. Tests in this package reveal evidence for causality based on the causality-by-functionality principle. 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 dependency not possible with symmetrical Pearson's chi-square or Fisher's exact tests.
Version: | 2.4.5 |
Depends: | R (≥ 3.0.0) |
Imports: | Rcpp, stats |
LinkingTo: | BH, Rcpp |
Suggests: | Ckmeans.1d.dp, testthat, knitr, rmarkdown |
Published: | 2018-02-20 |
Author: | Yang Zhang [aut], Hua Zhong [aut], Ruby Sharma [aut], Sajal Kumar [aut], Joe Song [aut, cre] |
Maintainer: | Joe Song <joemsong at cs.nmsu.edu> |
License: | LGPL (≥ 3) |
URL: | https://www.cs.nmsu.edu/~joemsong/publications |
NeedsCompilation: | yes |
Citation: | FunChisq citation info |
Materials: | NEWS |
CRAN checks: | FunChisq results |
Reference manual: | FunChisq.pdf |
Vignettes: |
Using the exact functional test Which quantity to measure functional dependency? |
Package source: | FunChisq_2.4.5.tar.gz |
Windows binaries: | r-devel: FunChisq_2.4.5.zip, r-release: FunChisq_2.4.5.zip, r-oldrel: FunChisq_2.4.4.zip |
OS X El Capitan binaries: | r-release: FunChisq_2.4.5.tgz |
OS X Mavericks binaries: | r-oldrel: FunChisq_2.4.3.tgz |
Old sources: | FunChisq archive |
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