hmat_sim {repfdr} | R Documentation |
A matrix of size 10000x3 of indicators of whether each z-score from zmat_sim
belongs to a non-null hypothesis for the feature in the study (1) or to a null hypothesis for the feature in the study (0).
data(hmat_sim)
hmat_sim
is a matrix of 10000 rows, each row a vector of the true association status from which the z-scores in the same row in zmat_sim
was generated. Specifically, for a zero entry in hmat_sim the corresponding z-score in zmat_sim
was generated from the standard normal distribution, and for a unit entry in hmat_sim the corresponding z-score in zmat_sim
was generated from the normal distribution with mean 3 and variance one.
#### use hmat_sim to generate the simulated z-scores: data(hmat_sim) m <- nrow(hmat_sim) set.seed(12) zmat_sim1 <- matrix(rnorm(n=3*m,mean=hmat_sim*3),nrow=m,ncol=3) rm(m,H) data(zmat_sim) stopifnot(all.equal(zmat_sim1,zmat_sim)) #### hmat_sim was generated by the following code: H <- hconfigs(n.studies= 3, n.association.status=2) f <- c(0.895,0.005,0.005,0.02,0.005,0.02,0.02,0.03) # frequencies for the association status vectors m = 10000 # number of tests in each study hmat_sim1 <- matrix(rep(x = H, times = m*cbind(f,f,f)),ncol=3) data(hmat_sim) stopifnot(all.equal(hmat_sim1,hmat_sim)) # the simulation design cbind(H,f) sum(f) # all sum to 1?