Package: FunChisq 2.5.4
FunChisq: Model-Free Functional Chi-Squared and Exact Tests
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.
Authors:
FunChisq_2.5.4.tar.gz
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FunChisq.pdf |FunChisq.html✨
FunChisq/json (API)
NEWS
# Install 'FunChisq' in R: |
install.packages('FunChisq', repos = c('https://joemsong.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 months agofrom:90eb2fc97b. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 07 2024 |
R-4.5-win-x86_64 | OK | Nov 07 2024 |
R-4.5-linux-x86_64 | OK | Nov 08 2024 |
R-4.4-win-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-x86_64 | OK | Nov 07 2024 |
R-4.4-mac-aarch64 | OK | Nov 07 2024 |
R-4.3-win-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-x86_64 | OK | Nov 07 2024 |
R-4.3-mac-aarch64 | OK | Nov 07 2024 |
Exports:add.candle.noiseadd.house.noiseadd.noisecond.fun.chisq.testcp.chisq.testcp.fun.chisq.testEFTDPEFTDQPfun.chisq.testplot_tablesimulate_tablestest.interactions
Adapted versus original functional chi-squared tests and conditional entropy
Rendered fromadapted.fun.chisq.test.Rmd
usingknitr::rmarkdown
on Nov 07 2024.Last update: 2023-05-25
Started: 2021-05-19
Examples of discrete patterns
Rendered frompatterns.Rmd
usingknitr::rmarkdown
on Nov 07 2024.Last update: 2023-05-25
Started: 2018-12-06
Measuring functional dependency model-free
Rendered fromfun.chisq.test.Rmd
usingknitr::rmarkdown
on Nov 07 2024.Last update: 2023-05-25
Started: 2016-04-22
Using the exact functional test
Rendered fromexact.fun.test.Rmd
usingknitr::rmarkdown
on Nov 07 2024.Last update: 2023-05-25
Started: 2016-05-02
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Model-Free Functional Chi-Squared and Exact Tests | FunChisq-package |
Apply Noise to Discrete-Valued Tables | add.candle.noise add.house.noise add.noise |
Conditional Functional Chi-Squared Test | cond.fun.chisq.test |
Comparative Chi-Squared Test for Model-Free Functional Heterogeneity | cp.fun.chisq.test |
Exact Functional Test on Two Discrete Random Variables | EFTDP EFTDQP Exact Functional Test |
Model-Free Functional Chi-Squared and Exact Tests | fun.chisq.test |
Deprecated Functions in Package 'FunChisq' | cp.chisq.test FunChisq-deprecated |
Plot a Table Using Color Intensity for Counts | plot_table |
Simulate Noisy Contingency Tables to Represent Diverse Discrete Patterns | simulate_tables |
Functional Chi-Squared Test of Functional Dependency among Many Variables in a Data Set | test.interactions |