Description Usage Arguments Value Author(s) References See Also
Given some parameters of the descendant hypotheses and ancestor hypotheses, return the critical function using the generalized hierarchical FDR controlling procedure under various type of dependence.
1 | hierFDR.CF(isTested, mi, li, l, depth, fdi, gdi, alpha, rOffset, type)
|
isTested |
logical; if |
mi |
the cardinality of the set of descendant hypotheses of H_i. |
li |
the number of leaf hypotheses in the set of descendant hypotheses H_i. |
l |
the total number of leaf hypotheses. |
depth |
the cardinality of the set of ancestor hypotheses of H_i, referred to as the depth of H_i. |
fdi |
the cardinality of the set of all hypotheses with the given depth. |
gdi |
the cardinality of the union set of all hypotheses with all depth no deeper than the given depth. |
alpha |
the significant level used to calculate the critical values to make decisions. |
rOffset |
the offset increment for the number of rejections. |
type |
the type of dependence structure of the hierarchically ordered hypotheses. Currently, we provide four types of dependence: |
A critical function of the index i and rejection number R.
Yalin Zhu
Lynch, G., Guo, W. (2016). On Procedures Controlling the FDR for Testing Hierarchically Ordered Hypotheses. arXiv preprint arXiv:1612.04467.
PositiveDeptCF
, ArbitraryDeptCF
, BlockPositiveCF
, BlockArbitraryCF
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