runfastcmh method.
makefastcmhdata(folder = "./", xfilename = "data.txt", yfilename = "label.txt", covfilename = "cov.txt", K = 2, L = 1000, n = 200, noiseP = 0.3, corruptP = 0.05, rho = 0.8, tau1 = 100, taulength1 = 4, tau2 = 200, taulength2 = 4, seednum = 2, truetaufilename = "truetau.txt", showOutput = FALSE, saveToList = FALSE)"./"."data.txt""label.txt"K numbers, where K is the
number of covariates. Default is "cov.txt"K=2.L=1000.n=200, i.e. 100 cases and 100 controls.noiseP=0.3corruptP of being flipped. Default is
corruptP=0.05.rho=0.8 (i.e. a very strong signal).tau1=100.taulength1=4, so default significant interval is [100, 103].tau2=200.taulength2=4, so default significant interval is
[200, 203].seednum=2."truetau.txt".FALSE, so will save to
folder by default. However, all of the examples use
saveToList=TRUE in order to avoid writing to file. The list will
consist of data, label and cov data frames, when
saveToList=TRUE.saveToList=FALSE.runfastcmh#make a small sample data set, using the default parameters
mylist <- makefastcmhdata(showOutput=TRUE, saveToList=TRUE)
#make a very small sample data set
mylist <- makefastcmhdata(n=20, L=10, tau1=2, taulength1=2,
tau2=6, taulength2=2, saveToList=TRUE)
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