dclong.spt m0, pi_0, compare with qvalue()

m0.bdn() example run, fdr

#simulate 1000 p-vlaues from a mixture beta and uniform distribution.

p = rbunif(1000, alpha=1, beta=29, gamma=0.7)

#estimate m0 using the method in Story and Tibshirani (2003).

m0.st(p)

#estimate m0 using the method in Nettleton et al. (2006)

m0.nhcw(p)

# ---------- a real example in Bancroft, Du and Nettleton (2013) --------------

# read in C++ source code

tsf_code = read_code("test_statistics.cpp")

# genrate function for sequential permutation test

# for no location difference between two samples

if(!exists("cxxspt.mean")){

    cxxwrapper(tsf_code, "abs_mean_diff0", "abs_mean_diff", c("n1", "", "int")) -> cxxspt.mean

}

# download data

if(!file.exists('spt_data.rda')){

    download.file('http://dclong.github.io/media/spt/spt_data.rda', 'spt_data.rda')

}

load('spt_data.rda')

cxxspt.mean(leukemia, 10, 1000, n1=5) -> cxxspt.out

#estimate m0 using the method in Bancroft, Du and Nettleton (2013).

m0.bdn(cxxspt.out, 20)

Using a example dataset of 1000 points

From qvalue(), $\pi_0$ = 0.662.