Ftest_LFM: Apply the Farmtest method to the Laplace factor model

In LFM: Laplace Factor Model Analysis and Evaluation

Apply the Farmtest method to the Laplace factor model

Description

This function simulates data from a Lapalce factor model and applies the FarmTest for multiple hypothesis testing. It calculates the false discovery rate (FDR) and power of the test.

Usage

Ftest_LFM(data, p1)

Arguments

data	A matrix or data frame of simulated or observed data from a Laplace factor model.
p1	The proportion of non-zero hypotheses.

Value

A list containing the following elements:

FDR	The false discovery rate, which is the proportion of false positives among all discoveries (rejected hypotheses).
Power	The statistical power of the test, which is the probability of correctly rejecting a false null hypothesis.
PValues	A vector of p-values associated with each hypothesis test.
RejectedHypotheses	The total number of hypotheses that were rejected by the FarmTest.

Examples

library(LaplacesDemon)
library(MASS)
n=1000
p=10
m=5
mu=t(matrix(rep(runif(p,0,1000),n),p,n))
mu0=as.matrix(runif(m,0))
sigma0=diag(runif(m,1))
F=matrix(mvrnorm(n,mu0,sigma0),nrow=n)
A=matrix(runif(p*m,-1,1),nrow=p)
lanor <- rlaplace(n*p,0,1)
epsilon=matrix(lanor,nrow=n)
D=diag(t(epsilon)%*%epsilon)
data=mu+F%*%t(A)+epsilon
p1=40
results <- Ftest_LFM(data, p1)
print(results$FDR)
print(results$Power)

LFM documentation built on April 16, 2025, 9:07 a.m.