empiricalEnrichmentMeanCDF {transite} | R Documentation

## Significance of Observed Mean

### Description

`empiricalEnrichmentMeanCDF` returns an estimate of the significance of the observed mean, given a vector of means based on random permutations of the data.

### Usage

    empiricalEnrichmentMeanCDF(random.means, actual.mean,
      alternative = c("two.sided", "less", "greater"), conf.level = 0.95)

### Arguments

`random.means` | numeric vector of means based on random permutations of the data (empirical null distribution)
`actual.mean` | observed mean
`alternative` | side of the test, one of the following: `"two.sided"`, `"less"`, `"greater"`
`conf.level` | confidence level for the returned confidence interval.

### Value

A list with the following components:

`p.value.estimate` | the estimated p-value of the observed mean
`conf.int` | the confidence interval around that estimate

### See Also

Other k-mer functions: `calculateKmerEnrichment`, `checkKmers`, `computeKmerEnrichment`, `drawVolcanoPlot`, `generateKmers`, `generatePermutedEnrichments`, `homopolymerCorrection`, `permTestGeometricMean`, `runKmerSPMA`, `runKmerTSMA`

### Examples

    test.sd <- 1.0
    test.null.distribution <- rnorm(n = 10000, mean = 1.0, sd = test.sd)

    empiricalEnrichmentMeanCDF(test.null.distribution, test.sd * 2, "greater")

[Package transite version 1.2.1 Index]