Ckmeans.1d.dp, DiffXTables, GridOnClusters, testthat, knitr,
rmarkdown

c(person("Yang", "Zhang", role = "aut"),
person("Hua", "Zhong", role = "aut",
comment = c(ORCID = "0000-0003-1962-2603")),
person("Hien", "Nguyen", role = "aut",
comment = c(ORCID = "0000-0002-7237-4752")),
person("Ruby", "Sharma", role = "aut",
comment = c(ORCID = "0000-0001-7774-4065")),
person("Sajal", "Kumar", role = "aut",
comment = c(ORCID = "0000-0003-0930-1582")),
person("Joe", "Song", role = c("aut", "cre"),
email = "joemsong@cs.nmsu.edu",
comment = c(ORCID = "0000-0002-6883-6547")))
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) <arXiv:1311.2707>,
an adapted functional chi-squared test, 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.
Ckmeans.1d.dp, DescTools, DiffXTables, GridOnClusters,
infotheo, knitr, rmarkdown, testthat