csmGmm (version 0.3.0)

symm_fit_cor_EM: symm_fit_cor.R

Description

Fit the correlated csmGmm for sets of correlated elements. Currently restricted to K=2.

Usage

symm_fit_cor_EM(
  testStats,
  corMat,
  initMuList,
  initPiList,
  eps = 10^(-5),
  checkpoint = TRUE
)

Value

A list with the elements:

muInfo

List with same dimensions as initMuList, holds the final mean parameters.

piInfo

List with same dimensions as initPiList, holds the final probability parameters.

iter

Number of iterations run in EM algorithm.

lfdrResults

J*1 vector of all lfdr statistics.

Arguments

testStats

J*K matrix of test statistics where J is the number of sets and K is number of elements in each set.

corMat

K*K matrix that describes the correlation structure of each set.

initMuList

List of 2^K elements where each element is a matrix with K rows and number of columns equal to the number of possible mean vectors for that binary group.

initPiList

List of 2^K elements where each element is a vector with number of elements equal to the number of possible mean vectors for that binary group.

eps

Scalar, stop the EM algorithm when L2 norm of difference in parameters is less than this value.

checkpoint

Boolean, set to TRUE to print iterations of EM.

Examples

set.seed(0)
corMat <- matrix(data=c(1, 0.3, 0.3, 1), nrow=2)
testStats <- rbind(mvtnorm::rmvnorm(n=200, mean=c(3, 0), sigma=corMat),
mvtnorm::rmvnorm(n=200, mean=c(0, 4), sigma=corMat),
mvtnorm::rmvnorm(n=100, mean=c(7, 7), sigma=corMat),
mvtnorm::rmvnorm(n=10^4 - 500, mean=c(0, 0), sigma=corMat))
initMuList <- list(matrix(data=0, nrow=2, ncol=1), matrix(data=c(0, 3), nrow=2),
matrix(data=c(4, 0), nrow=2), matrix(data=c(5, 5), nrow=2))
initPiList <- list(c(0.9), c(0.04), c(0.04), c(0.02))
results <- symm_fit_cor_EM(testStats = testStats, corMat = cor(testStats),
initMuList = initMuList, initPiList = initPiList)