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FDX (version 2.0.0)

FDX-package: 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).

Arguments

Author

Maintainer: Florian Junge florian.junge@h-da.de

Authors:

  • Sebastian Döhler

Other contributors:

  • Etienne Roquain [contributor]

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.

References

Döhler, S. & Roquain, E. (2020). Controlling False Discovery Exceedance for Heterogeneous Tests. Electronic Journal of Statistics, 14(2), pp. 4244-4272. tools:::Rd_expr_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. tools:::Rd_expr_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. (eletronic). tools:::Rd_expr_doi("10.2202/1544-6115.1247")

See Also