FDX-package {FDX} | R Documentation |
False Discovery Exceedance (FDX) Control for Heterogeneous and Discrete Tests
Description
This package implements the [HLR], [HGR] and [HPB] procedures for both heterogeneous and discrete tests (see Reference).
Details
The functions are reorganized from the reference paper in the following way.
discrete.LR()
(for Discrete Lehmann-Romano) implements [DLR],
discrete.GR()
(for Discrete Guo-Romano) implements [DGR] and
discrete.PB()
(for Discrete Poisson-Binomial) implements [DPB].
DLR()
and NDLR()
are wrappers for discrete.LR()
to access
[DLR] and its non-adaptive version directly. Likewise, DGR()
,
NDGR()
, DPB()
and NDPB()
are wrappers for
discrete.GR()
and discrete.PB()
, respectively. Their main
parameters are a vector of raw observed p-values and a list of the same
length, whose elements are the discrete supports of the CDFs of the p-values.
In the same fashion, weighted.LR()
(for Weighted Lehmann-Romano),
weighted.GR()
(for Weighted Guo-Romano) and weighted.PB()
(for Weighted Poisson-Binomial) implement [wLR], [wGR] and [wGR],
respectively. They also possess wrapper functions, namely wLR.AM()
,
wGR.AM()
and wPB.AM()
for arithmetic weighting, and wLR.GM()
,
wPB.GM()
and wPB.GM()
for geometric weighting.
The functions fast.Discrete.LR()
, fast.Discrete.GR()
and fast.Discrete.PB()
are wrappers for
DiscreteFDR::fisher.pvalues.support()
and discrete.LR()
,
discrete.GR()
and discrete.PB()
, respectively, which allow to apply
discrete procedures directly to a data set of contingency tables.
Author(s)
Maintainer: Florian Junge diso.fbmn@h-da.de (ORCID)
Authors:
Sebastian Döhler sebastian.doehler@h-da.de (ORCID)
Other contributors:
Etienne Roquain [contributor]
References
Döhler, S. & Roquain, E. (2020). Controlling False Discovery Exceedance for Heterogeneous Tests. Electronic Journal of Statistics, 14(2), pp. 4244-4272. doi:10.1214/20-EJS1771
Lehmann, E. L. & Romano, J. P. (2005). Generalizations of the familywise error rate. The Annals of Statistics, 33(3), pp. 1138-1154. doi:10.1214/009053605000000084
Guo, W. & Romano, J. P. (2007). A generalized Sidak-Holm procedure and control of generalized error rates under independence. Statistical Applications in Genetics and Molecular Biology, 6(1), Art. 3, 35 pp. (electronic). doi:10.2202/1544-6115.1247
See Also
Useful links: