| SEL.caution.parameter {LFDREmpiricalBayes} | R Documentation |
Based on a Decision-Theoretic Approach, Performs a Multiple Hyothesis Testing Problem under an Squared Error Loss Function
Description
Assuming a squared error loss function, it provides three caution-type actions using estimated LFDRs computed based on both separate and combined reference classes.
Usage
SEL.caution.parameter(x1,x2)
Arguments
x1 |
Input numeric vector of LFDR estimates in the separate reference class. |
x2 |
Input numeric vector of LFDR estimates in the combined reference class. |
Value
Much like caution.parameter.actions, this function returns three vectors
of equal size as seen below:
CGM1 |
Squared error loss value for the Conditional Gamma Minimax (CGMinimax). |
CGM0 |
Squared error loss value for the Conditional Gamma Minimin (CGMinimin). |
CGM0.5 |
Squared error loss value for the Action/Decision estimate (a balance between CGMinimax and CGMinimin. |
For each index of the vectors, the squared error loss values are given.
Author(s)
Code: Ali Karimnezhad.
Documentation: Johnary Kim and Anna Akpawu.
References
Karimnezhad, A. and Bickel, D. R. (2016). Incorporating prior knowledge about genetic variants into the analysis of genetic association data: An empirical Bayes approach. Working paper. Retrieved from http://hdl.handle.net/10393/34889
Examples
#Similar to caution.parameter actions we have the following classes
#First reference class
LFDR.Separate <- c(0.14, 0.8, 0.16, 0.30)
#Second reference class
LFDR.Combined <- c(0.21, 0.61, 0.12, 0.10)
output <- SEL.caution.parameter(LFDR.Separate, LFDR.Combined)
# Three caution cases with SEL values.
output