null_perm_m0 {trc} | R Documentation |
Procedure for estimating the null distribution of the TRC tau with a given m value
Description
Procedure for estimating the null distribution of the TRC tau with a given m value.
Usage
null_perm_m0(X,Y,nperm=1000,m=5,seed=21)
Arguments
X |
An observed data vector from the first condition. |
Y |
An observed data vector from the second condition. |
nperm |
the number of permutations to estimate the null distribution (default: 1000). |
m |
A rank threshold for the calculation of TRC tau (default: 5). |
seed |
An initial seed for the permutation. |
Details
Null distribution of the TRC tau with a given m value is estimated by the permuted samples.
Value
perm_tau |
A vector of calculated TRC tau values from the permuted samples |
References
Lim, J., Yu, D., Kuo, H., Choi, H., and Walmsely, S. (2019). Truncated Rank Correlation as a robust measure of test-retest reliability in mass spectrometry data. Statistical Applications in Genetics and Molecular Biology, 18(4).
Examples
p = 100
sig_z = 1.15
sig_e = 1
mu_z = 2
mu_e = 8
m0 = 30
S1 = rnorm(p,mean=mu_e,sd=sig_e)
S2 = rnorm(p,mean=mu_e,sd=sig_e)
if(m0!=0)
{
X = mu_z + rnorm(m0,mean=0,sd=sig_z)
indx = 1:p
s_indx = sort(sample(indx,m0))
S1[s_indx] = S1[s_indx] + X
S2[s_indx] = S2[s_indx] + X
}
S1 = exp(S1)
S2 = exp(S2)
null_res = null_perm_m0(S1,S2,nperm=1000,m=5,seed=21)
[Package trc version 0.2 Index]