Description Usage Arguments Details Value See Also Examples

View source: R/weightedLR_fun.R

Apply the weighted [wLR] procedure, with or without computing the critical values, to a set of p-values. Both arithmetic and geometric weighting are available.

1 2 3 4 5 6 7 8 9 10 11 12 |

`raw.pvalues` |
vector of the raw observed p-values, as provided by the end user and before matching with their nearest neighbor in the CDFs supports. |

`weights` |
a numeric vector. Contains the weights of the p-values. |

`alpha` |
the target FDP, a number strictly between 0 and 1. For |

`zeta` |
the target probability of not exceeding the desired FDP, a number strictly between 0 and 1. If |

`weighting.method` |
a character string specifying whether to conduct arithmetic ( |

`critical.values` |
a boolean. If |

`wLR.AM`

and `wLR.GM`

are wrapper functions for `weighted.LR`

.
The first one simply passes all its parameters to `weighted.LR`

with
`weighting.method = "AM"`

and `wLR.GM`

does the same with
`weighting.method = "GM"`

.

A `FDX`

S3 class object whose elements are:

`Rejected` |
Rejected raw p-values. |

`Indices` |
Indices of rejected hypotheses. |

`Num.rejected` |
Number of rejections. |

`Adjusted` |
Adjusted p-values (only for step-down direction). |

`Weighted` |
Weighted p-values. |

`Critical.values` |
Critical values (if requested). |

`Method` |
A character string describing the used algorithm, e.g. 'Discrete Lehmann-Romano procedure (step-up)'. |

`FDP.threshold` |
FDP threshold |

`Exceedance.probability` |
Probability |

`Weighting` |
A character string describing the weighting method. |

`Data$raw.pvalues` |
The values of |

`Data$weights` |
The values of |

`Data$data.name` |
The respective variable names of |

`kernel`

, `FDX-package`

, `continuous.LR`

,
`continuous.GR`

, `discrete.LR`

,
`discrete.GR`

, `discrete.PB`

,
`weighted.GR`

, `weighted.PB`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
# Construction of the p-values and their supports for weighted methods
raw.pvalues.weighted <- c(0.7389727, 0.1882310, 0.1302457, 0.9513677,
0.7592122, 0.0100559, 0.0000027, 0.1651034)
weights <- c(0.7947122, 1.2633867, 2.8097858, 2.2112801,
2.3878654, 1.2389620, 2.3878654, 0.7947122)
wLR.AM.fast <- wLR.AM(raw.pvalues.weighted, weights)
summary(wLR.AM.fast)
wLR.AM.crit <- wLR.AM(raw.pvalues.weighted, weights, critical.values = TRUE)
summary(wLR.AM.crit)
wLR.GM.fast <- wLR.GM(raw.pvalues.weighted, weights)
summary(wLR.GM.fast)
wLR.GM.crit <- wLR.GM(raw.pvalues.weighted, weights, critical.values = TRUE)
summary(wLR.GM.crit)
``` |

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