.fdr.qu {randRotation} | R Documentation

## Internal functions for p-value and FDR estimation

### Description

Internal functions for p-value and FDR estimation

### Usage

    .fdr.qu(
      s0,
      stats,
      beta = 0.05,
      na.rm = FALSE,
      ref.vector = sort(s0, decreasing = TRUE, na.last = TRUE)
    )

    .fdr.q(
      s0,
      stats,
      beta = 0.05,
      na.rm = FALSE,
      ref.vector = sort(s0, decreasing = TRUE, na.last = TRUE)
    )

    .pFdr(s0, stats, method, pooled, na.rm, beta)

### Arguments

`s0` | `numeric` vector of original (non-rotated) statistics.
`stats` | `numeric` matrix of rotated statistics.
`beta` | `numeric` between 0 and 1. See (Yekutieli and Benjamini 1999).
`na.rm` | `logical`. Should missing values be removed ?
`ref.vector` | Reference vector defining at which grid points of `s0` and (`stats`) the FDRs are approximated. All other points are approximated by spline interpolation. NAs are removed from ref.vector
`method` | A p-value or FDR adjustment method, see `pFdr`.
`pooled` | `logical`. `TRUE` if marginal distributions are exchangeable for all features so that rotated stats can be pooled, see `pFdr`.

### Value

`numeric` vector of (adjusted) p-value or FDR estimations for `s0`.

### References

Yekutieli D, Benjamini Y (1999). “Resampling-based false discovery rate controlling multiple test procedures for correlated test statistics.” Journal of Statistical Planning and Inference, 82(1-2), 171–196. ISSN 03783758, doi: 10.1016/S0378-3758(99)00041-5, https://doi.org/10.1016/S0378-3758(99)00041-5.

[Package randRotation version 1.2.2 Index]