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FunChisq
View on CRAN: Click
here
Download and install FunChisq package within the R console
Install from CRAN:
install.packages("FunChisq")
Install from Github:
library("remotes")
install_github("cran/FunChisq") Install by package version:
library("remotes")
install_version("FunChisq", "2.5.4") Attach the package and use:
library("FunChisq")
Maintained by
Joe Song
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-03-08
Latest Update: 2024-05-10
Description:
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) ,
an adapted functional chi-squared test (Kumar & Song 2022)
,
and an exact functional test (Zhong & Song 2019)
(Nguyen et al. 2020)
. 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) . A
function index (Zhong & Song 2019)
(Kumar et al. 2018)
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.
How to cite:
Joe Song (2014). FunChisq: Model-Free Functional Chi-Squared and Exact Tests. R package version 2.5.4, https://cran.r-project.org/web/packages/FunChisq. Accessed 08 Oct. 2026.
Previous versions and publish date:
1.0 (2014-03-08 00:30), 2.0.0 (2015-02-16 17:39), 2.0.1 (2015-02-24 09:00), 2.0.2 (2015-03-04 14:57), 2.1.0 (2015-06-29 19:25), 2.2.0 (2016-01-24 15:45), 2.2.1 (2016-01-26 00:43), 2.2.2 (2016-02-14 23:05), 2.2.3 (2016-04-01 10:08), 2.2.4 (2016-04-22 08:40), 2.3.1 (2016-05-02 06:24), 2.3.2 (2016-09-02 02:18), 2.3.3 (2016-09-02 21:23), 2.4.0 (2017-02-28 10:58), 2.4.2 (2017-04-24 07:47), 2.4.3 (2017-05-02 18:17), 2.4.4 (2018-02-06 07:25), 2.4.5-1 (2018-06-16 07:15), 2.4.5-2 (2018-10-23 07:50), 2.4.5-3 (2018-12-06 14:50), 2.4.5 (2018-02-20 20:26), 2.4.8-1 (2019-09-08 18:20), 2.4.9.1 (2019-09-24 17:50), 2.4.9.2 (2020-03-14 18:30), 2.5.0 (2020-04-25 01:10), 2.5.1 (2020-06-14 08:20), 2.5.2 (2021-05-19 23:00), 2.5.3 (2023-05-25 12:30), (2026-07-09 08:04)
Other packages that cited FunChisq R package
View FunChisq citation profile
Other R packages that FunChisq depends,
imports, suggests or enhances
Complete documentation for FunChisq
Functions, R codes and Examples using
the FunChisq R package
Some associated functions: EFT . FunChisq-deprecated . FunChisq-package . cond.fun.chisq.test . cp.fun.chisq.test . fun.chisq.test . noise_model . plot_table . simulate_tables . test.interactions .
Some associated R codes: AdpFunChisq.R . CPChisq.R . CPFunChisq.R . CondFunChisq.R . FunChisq.R . Interaction.R . RcppExports.R . noise_model.R . plot_table.R . simulate_p_value.R . simulate_tables.R . Full FunChisq package functions and examples
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