weighted.LR {FDX} | R Documentation |
Weighted Lehmann-Romano Procedure
Description
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.
Usage
weighted.LR(
raw.pvalues,
weights,
alpha = 0.05,
zeta = 0.5,
weighting.method = "AM",
critical.values = FALSE
)
wLR.AM(raw.pvalues, weights, alpha = 0.05, zeta = 0.5, critical.values = FALSE)
wLR.GM(raw.pvalues, weights, alpha = 0.05, zeta = 0.5, critical.values = FALSE)
Arguments
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 |
Details
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"
.
Value
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 |
See Also
kernel
, FDX-package
, continuous.LR
,
continuous.GR
, discrete.LR
,
discrete.GR
, discrete.PB
,
weighted.GR
, weighted.PB
Examples
# 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)