Model-Free Functional Chi-Squared and Exact Tests R package FunChisq version 2.5.4 Statistical hypothesis testing methods for inferring model-free functional dependency using asymptotic chi-squared or exact distributions. Functional test statistics 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-squared tests (Zhang & Song 2013) <doi:10.48550/arXiv.1311.2707>, an adapted functional chi-squared test (Kumar & Song 2022) <doi:10.1093/bioinformatics/btac206>, and an exact functional test (Zhong & Song 2019) <doi:10.1109/TCBB.2018.2809743> (Nguyen et al. 2020) <doi:10.24963/ijcai.2020/372>. The normalized functional chi-squared test was used by Best Performer 'NMSUSongLab' in HPN-DREAM (DREAM8) Breast Cancer Network Inference Challenges (Hill et al. 2016) <doi:10.1038/nmeth.3773>. A function index (Zhong & Song 2019) <doi:10.1186/s12920-019-0565-9> (Kumar et al. 2018) <doi:10.1109/BIBM.2018.8621502> derived from the functional test statistic offers a new effect size measure for the strength of functional dependency, a better alternative to conditional entropy in many aspects. 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-squared or Fisher's exact tests. Software Depends: R (>= 3.0.0) Imports: Rcpp, Rdpack (>= 0.6-1), stats, dqrng LinkingTo: BH, Rcpp Suggests: Ckmeans.1d.dp, DescTools, DiffXTables, GridOnClusters, infotheo, knitr, rmarkdown, testthat (>= 3.0.0) Joe Song <joemsong@cs.nmsu.edu> Comprehensive R Archive Network (CRAN) Yang Zhang [aut], Hua Zhong [aut] (ORCID: <https://orcid.org/0000-0003-1962-2603>), Hien Nguyen [aut] (ORCID: <https://orcid.org/0000-0002-7237-4752>), Ruby Sharma [aut] (ORCID: <https://orcid.org/0000-0001-7774-4065>), Sajal Kumar [aut] (ORCID: <https://orcid.org/0000-0003-0930-1582>), Yiyi Li [aut] (ORCID: <https://orcid.org/0000-0001-8859-3987>), Joe Song [aut, cre] (ORCID: <https://orcid.org/0000-0002-6883-6547>) LGPL (>= 3) 2024-05-10 application/tgz https://CRAN.R-project.org/package=FunChisq doi:10.32614/CRAN.package.FunChisq