HighProbability estimates which alternative hypotheses have frequentist or Bayesian probabilities at least as great as a specified threshold, given a list of p-values.
Overview
HighProbability provides a simple, fast, reliable solution to the multiple testing problem. Given a vector of p-values or achieved significance levels computed using standard frequentist inference, HighProbability determines which ones are low enough that their alternative hypotheses can be considered highly probable. The p-value vector may be determined using existing R functions such as t.test, wilcox.test, cor.test, or sample. HighProbability can be used to detect differential gene expression and to solve other problems involving a large number of hypothesis tests.
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Documentation
- Help pages
- 2
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
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- Return-value docs
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- Help pages citing references
- 50%
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Code & Tests
People & History
Package metadata
- First published
- 1977-08-08
- Total releases
- 2
- License
- Mozilla Public License 1.1 (http://www.mozilla.org/MPL/)
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