knockoffDMC: Group knockoffs of discrete Markov chains
In SNPknock: Knockoffs for Hidden Markov Models and Genetic Data

Description Usage Arguments Details Value References See Also Examples

This function constructs knockoffs of variables distributed as a discrete Markov chain.

1 2	knockoffDMC(X, pInit, Q, groups = NULL, seed = 123, cluster = NULL, display_progress = FALSE)

`X`	an integer matrix of size n-by-p containing the original variables.
`pInit`	an array of length K, containing the marginal distribution of the states for the first variable.
`Q`	an array of size (p-1,K,K), containing a list of p-1 transition matrices between the K states of the Markov chain.
`groups`	an array of length p, describing the group membership of each variable (default: NULL).
`seed`	an integer random seed (default: 123).
`cluster`	a computing cluster object created by makeCluster (default: NULL).
`display_progress`	whether to show progress bar (default: FALSE).

Each element of the matrix X should be an integer value between 0 and K-1. The transition matrices contained in Q are defined such that P[X_{j+1}=k|X_{j}=l]=Q[j,l,k].

An integer matrix of size n-by-p containing the knockoff variables.

\insertRef

sesia2019SNPknock \insertRefsesia2019multiSNPknock

Other knockoffs: knockoffGenotypes, knockoffHMM, knockoffHaplotypes

# Generate data
p = 10; K = 5;
pInit = rep(1/K,K)
Q = array(stats::runif((p-1)*K*K),c(p-1,K,K))
for(j in 1:(p-1)) { Q[j,,] = Q[j,,] / rowSums(Q[j,,]) }
X = sampleDMC(pInit, Q, n=20)
# Generate knockoffs
Xk = knockoffDMC(X, pInit, Q)
# Generate group-knockoffs for groups of size 3
groups = rep(seq(p), each=3, length.out=p)
Xk = knockoffDMC(X, pInit, Q, groups=groups)