| summary.p.fdr {FDRestimation} | R Documentation |
Summary of p.fdr.object
Description
This function summarizes a p.fdr object.
Usage
## S3 method for class 'p.fdr'
summary(object, digits = 5, ...)
Arguments
object |
A list of output from the p.fdr function. |
digits |
A numeric value for the number of desired digits in the summary output. Defaults to 3. |
... |
Additional arguments affecting the summary produced. |
Details
We run into errors or warnings when
Value
A list containing the following components:
Range |
The range on the false discovery rates. |
Significant Findings |
The number of significant findings. Found using the adjusted p-values and the given threshold. This is also the number of times we decide to reject the null hypothesis that the data is generated from a standard normal distribution. |
Inconclusive Findings |
The number of inconclusive findings. Found using the adjusted p-values and the given threshold. This is also the number of times we fail to reject the null hypothesis that the data is generated from a standard normal distribution. |
Assumed/Estimated pi0 |
the assumed or estimated pi0 value depending on how the p.fdr function was run. |
Number of Tests |
The total number of multiple comparison tests completed. |
Adjustment Method |
The adjustment method used in the p.fdr function. |
References
Romain Francois (2014). bibtex: bibtex parser. R package version 0.4.0.
R Core Team (2016). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, https://www.R-project.org/.
Murray MH, Blume JD (2020). “False Discovery Rate Computation: Illustrations and Modifications.” 2010.04680.
See Also
Examples
# Example 1
pi0 = 0.8
pi1 = 1-pi0
n = 10
n.0 = ceiling(n*pi0)
n.1 = n-n.0
sim.data = c(rnorm(n.1,5,1),rnorm(n.0,0,1))
sim.data.p = 2*pnorm(-abs(sim.data))
fdr.output = p.fdr(pvalues=sim.data.p, adjust.method="BH")
summary(fdr.output)