Package: SetTest 0.3.0
SetTest: Group Testing Procedures for Signal Detection and Goodness-of-Fit
It provides cumulative distribution function (CDF), quantile, p-value, statistical power calculator and random number generator for a collection of group-testing procedures, including the Higher Criticism tests, the one-sided Kolmogorov-Smirnov tests, the one-sided Berk-Jones tests, the one-sided phi-divergence tests, etc. The input are a group of p-values. The null hypothesis is that they are i.i.d. Uniform(0,1). In the context of signal detection, the null hypothesis means no signals. In the context of the goodness-of-fit testing, which contrasts a group of i.i.d. random variables to a given continuous distribution, the input p-values can be obtained by the CDF transformation. The null hypothesis means that these random variables follow the given distribution. For reference, see [1]Hong Zhang, Jiashun Jin and Zheyang Wu. "Distributions and power of optimal signal-detection statistics in finite case", IEEE Transactions on Signal Processing (2020) 68, 1021-1033; [2] Hong Zhang and Zheyang Wu. "The general goodness-of-fit tests for correlated data", Computational Statistics & Data Analysis (2022) 167, 107379.
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SetTest_0.3.0.tar.gz
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SetTest.pdf |SetTest.html✨
SetTest/json (API)
# Install 'SetTest' in R: |
install.packages('SetTest', repos = c('https://wpihongzhang.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 4 months agofrom:191c7818bb. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 13 2024 |
R-4.5-win | OK | Nov 13 2024 |
R-4.5-linux | OK | Nov 13 2024 |
R-4.4-win | OK | Nov 13 2024 |
R-4.4-mac | OK | Nov 13 2024 |
R-4.3-win | OK | Nov 13 2024 |
R-4.3-mac | OK | Nov 13 2024 |
Exports:pbjphcpower.bjpower.hcpower.phipphipphi.omniqbjqhcqphistat.bjstat.hcstat.phistat.phi.omnitest.bjtest.hctest.phitest.phi.omni
Dependencies: