get.masterpool.cv.fold.data: Splits masterpool testing data into crossvalidation data sets

In gregorkb/aenetgt: Adaptive Elastic Net for Group Testing Data

Splits masterpool testing data into crossvalidation data sets

Description

Splits masterpool testing data into crossvalidation data sets

Usage

get.masterpool.cv.fold.data(X, Y, Z, K)

Arguments

X	Design matrix with first column a column of 1s.
Y	Group testing output from one of the functions individual.assay.gen, masterpool.assay.gen, dorfman.assay.gen, or array.assay.gen.
Z	Group testing output from one of the functions individual.assay.gen, masterpool.assay.gen, dorfman.assay.gen, or array.assay.gen.
K	The number of crossvalidation folds.

Value

List of length K of the crossvalidation training and testing data sets.

Examples

# generate individual covariate values and disease statuses
N <- 160
data <- model1(N)
X <- data$X
Y.true <- data$Yi
Se <- c(.95) # set master pool assay sensitivity
Sp <- c(.97) # set master pool assay specificity
cj <- 4 # set size of master pools
# subject individuals to master pool testing
assay.data <- masterpool.assay.gen(Y.true,Se,Sp,cj)
Z <- assay.data$Z
Y <- assay.data$Y
masterpool.cv.fold.data <- get.masterpool.cv.fold.data(X,Y,Z,K=5)

gregorkb/aenetgt documentation built on Oct. 12, 2022, 11:51 a.m.